3 paragraphs

Campaign Communications in U.S. Congressional Elections

Author(s): JAMES N. DRUCKMAN, MARTIN J. KIFER and MICHAEL PARKIN

Source: The American Political Science Review , August 2009, Vol. 103, No. 3 (August 2009), pp. 343-366

Published by: American Political Science Association

Stable URL: https://www.jstor.org/stable/27798510

REFERENCES Linked references are available on JSTOR for this article: https://www.jstor.org/stable/27798510?seq=1&cid=pdf- reference#references_tab_contents You may need to log in to JSTOR to access the linked references.

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at https://about.jstor.org/terms

American Political Science Association is collaborating with JSTOR to digitize, preserve and extend access to The American Political Science Review

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3 August 2009 doi:10.1017/S0003055409990037

Campaign Communications in U.S. Congressional Elections JAMES N. DRUCKMAN Northwestern University

MARTIN J. KIFER High Point University MICHAEL PARKIN Oberlin College

lectoral campaigns are the foundation of democratic governance; yet scholarship on the content of campaign communications remains underdeveloped. In this paper, we advance research on

* J U.S. congressional campaigns by integrating and extending extant theories of campaign commu nication. We test the resulting predictions with a novel dataset based on candidate Web sites over three election cycles. Unlike television advertisements or newspaper coverage, Web sites provide an unmediated, holistic, and representative portrait of campaigns. We find that incumbents and challengers differ across a broad range of behavior that reflects varying attitudes toward risk, that incumbents' strategies depend on the competitiveness of the race, and that candidates link negative campaigning to other aspects of their rhetorical strategies. Our efforts provide researchers with a basis for moving toward a more complete understanding of congressional campaigns.

Electoral campaigns are a defining feature of democratic polities. Yet scholarship on electoral campaigns, particularly on the content of cam

paign communications, remains disjointed. The field has not changed very much since Riker's (1996, 4) description over a decade ago: "we have very little knowledge about the rhetorical content of campaigns, which is, however, their principal feature ... the fact remains that we know very little about what to say in campaigns?but this is what both political scientists and candidates want to know." Shortcomings are par ticularly acute in the United States for nonpresiden tial campaigns. "From reading our literature," notes Perloff (2002, 621), "you would assume that the only campaigns in America are for the presidency."

In what follows, we advance research on campaigns, focusing on communication in U.S. congressional cam paigns. We begin by offering a framework for studying campaign communication that integrates and extends prior work. The analysis focuses on the extent to which candidates take risks or play it safe in their campaign strategies. We test expectations from the framework

James N. Druckman is Associate Professor of Political Science and

Faculty Fellow at the Institute for Policy Research, Northwestern University, 601 University Place, Evanston, IL 60208 (druckman@ northwestern.edu).

Martin J. Kifer is Assistant Professor of Political Science and Di rector of the Survey Research Center, High Point University, 833

Montlieu Avenue, High Point, NC 27262 (mkifer@highpoint.edu). Michael Parkin is Assistant Professor of Politics, Oberlin

College, 10 N. Professor Street, Oberlin, OH 44074 (Michael. Parkin@oberlin.edu).

We thank Nora Paul and Brian Southwell for critical guid ance in constructing our original coding framework, Gary Jacobson for providing candidate background data, and the dozens of individuals who assisted in data collection. We also thank Lonna Atkeson, Amber Wichowsky, and many others for providing advice. We owe a special debt of gratitude to the APSR's reviewers and editors for insightful guidance that fun damentally shaped all aspects of the paper. Support for this re search was provided by the University of Minnesota McKnight Land-Grant Professorship, Northwestern University's AT&T Re search Scholar Fund, and, for the survey of website designers, the National Science Foundation (SES-0822819 and SES-0822819). Au thors' names are listed in alphabetical order.

with new data based on candidate Web sites over time, which offer an unmediated, holistic, and representa tive portrait of campaigns. The view from these data significantly differs from that of previous studies that rely on advertising and newspaper stories to study can didate behavior. Our efforts provide researchers with a foundation for moving toward a more complete un derstanding of congressional campaigns.

CONGRESSIONAL CAMPAIGN RHETORICAL STRATEGY

In many ways, the literature on congressional cam paigns is progressive and wide-ranging. Scholars de vote considerable attention to distinct topics, such as going negative, issue ownership, and position-taking (Franklin 1991; Lau and Pomper 2004; Petrocik 1996). They also have identified important determinants of campaign strategy?most notably, showing how com petition and incumbency influence rhetorical choices (Kahn and Kenney 1999; Trent and Friedenberg 2008).

We aim to bring these various strands of the literature together (e.g., work on negativity and issue owner ship) while also generating additional insights into cam paigns' rhetorical choices. We start with a set of widely agreed-upon premises about congressional campaign behavior, from which we deduce empirical predictions.

First, a primary purpose of campaign rhetoric is to es tablish the criteria on which voters base their decisions.

Campaigns attempt to do this by emphasizing or high lighting their preferred criteria. Evidence on this point comes from an array of literatures, including work on priming (Miller and Krosnick 1996), issue ownership (Petrocik 1996), heresthetics (Riker 1996), campaigns (Berelson, Lazarsfeld, and McPhee 1954; Schattschnei der 1960), and political polling (Druckman, Jacobs, and Ostermeier 2004; Jacobs and Shapiro 1994). Second, when it comes to congressional elections, voters tend to base their decisions on incumbency, issues, candi dates' personal features, and/or party (Druckman 2004; Niemi and Weisberg 1993, 99; Rahn et al. 1990). It follows from these two premises that campaigns will

343

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

emphasize incumbency, issues, personal features, and/or partisanship, depending on which of these cri teria they wish voters to use.

Third, half a century of voting research shows that voters pay scant attention to campaign rhetoric, and base their decisions on a subset of accessible consider

ations (Iyengar and Kinder 1987; Kinder 1998; Zaller 1992). Fourth, in congressional elections, incumbency serves as a highly accessible basis of vote choice; all else constant, voters favor incumbents (Gronke 2000, 140-41). This manifests itself in the well-known ben efit from incumbency that provides incumbents with up to a 10-percentage-point advantage (Abramowitz, Alexander, and Gunning 2006; Ansolabehere and Snyder 2004, 487). The incumbency advantage stems, in part, from three particular candidate characteristics: voters find incumbents appealing because they pos sess experience in office, are familiar (e.g., have ties to the district), and have provided benefits for the dis trict or state (e.g., organizing events concerning a lo cal issue, casework, pork-barrel projects) (e.g., Fiorina 1989; Gronke 2000; Jacobson 2004). These assumptions imply that incumbents will emphasize experience, fa

miliarity, and benefits, and that candidates who are not advantaged?i.e. challengers?have an incentive to (a) induce voters to attend to rhetoric and (b) use the rhetoric to cause voters to base their decisions on cri

teria other than incumbency. Our final premise concerns ways in which candidates

motivate voters to attend to rhetoric. One well-known

approach is to employ negative language (i.e., "go neg ative"). Evidence on the attention-grabbing nature of negativity comes from political psychology research (Druckman and McDermott 2008; Marcus, Newman, and MacKuen 2000), as well as a long line of work in psychology showing that individuals pay more atten tion and give more weight to negative than to positive information (e.g., people attend more when told of 5% unemployment than when told of 95% employ ment) (Baumeister et al. 2001; Wason 1959).1 Another way to stimulate attention that has become relevant in recent years is to engage voters by using new media technologies (Buey 2004). This includes, for example, allowing Web site visitors to adjust content and/or in terpersonally communicate with the campaign and/or other voters (e.g., message boards, forums, live chats, interactive blogs). Just as with negativity, extant re search shows that allowing interaction stimulates atten tion and information-seeking behavior (e.g., Southwell and Lee 2004, 645).

From these premises, we deduce a set of predictions. First, compared to incumbents, challengers will employ significantly more negative rhetoric and provide more opportunities for voters to engage with the campaign (i.e., through interactive Internet technologies). The goal is to induce voters to attend to new information (also see Kahn and Kenney 1999, 2004). Second, com pared to incumbents, challengers will put significantly more emphasis on issues, personal features, and party

1 Campaigns also appear to recognize the value of negative informa tion in prompting attention and affecting voters (e.g., Kern 1989).

affiliation. They will do so in an attempt to shift vot ers' focus away from incumbency towards alternative criteria (see, e.g., Groseclose 2001). Issue strategies in clude emphasizing or priming issues that advantage the candidate (e.g., issues "owned" by the candidate's party), stating unambiguous issue positions that en able voters to evaluate the candidate, and publicizing endorsements from policy-oriented groups that voters can use as issue shortcuts (Downs 1957; Lupia and

McCubbins 1998; Sniderman, Brody, and Tetlock 1991, 93-120). Strategies focusing on personal features in clude discussing leadership, competence, and empathy (e.g., Fenno 1978; Funk 1999; Kinder 1986), as well as

making reference to polls that demonstrate the candi date's viability and standing in the public's eyes (Lau and Redlawsk 2006).

Our third hypothesis is that, compared to chal lengers, incumbents will put significantly more em phasis on experience in public office, familiarity, and providing district or state benefits; as mentioned, these factors underlie the incumbent's advantage. A caveat to this prediction is that safe incumbents have little incentive to campaign actively. Incumbents enjoy an inherent advantage and, all else constant, prefer that voters do not pay attention to campaign rhetoric. In noncompetitive races?where voters often ignore the campaign (e.g., Kahn and Kenney 1999,182-83)?safe incumbents will opt to be silent on the campaign trail, refusing to engage in active advocacy (for fear of ap pearing insecure about the campaign) (Jacobson 2004, 97; Trent and Friedenberg 2008, 100). In this case, in cumbents will not necessarily put more emphasis than challengers on incumbency factors. As a campaign be comes increasingly competitive, however, incumbents have little choice but to enter the fray and increase the relative emphasis on their advantages, particularly aspects of incumbency.

Our predictions echo extant work by identifying incumbency-challenger status as a critical determi nant of campaign behavior over a range of strategies (Jacobson 2004, 91-98; Latimer 2007; Trent and Friedenberg 2008; 86-118) with competition playing a moderating role (Kahn and Kenney 1999; 93-97). As will soon be clear, our predictions also extend to a broad range of strategies that either are treated within distinct frameworks (e.g., going negative and issue ownership) or are not widely studied (e.g., the use of polls, endorsements, partisanship, personal feature emphasis, aspects of incumbency) (Lin 2004). Moreover, there is an underlying dynamic that we

believe ties our predictions together. The distinction between incumbent and challenger strategies amounts to variation in risk-taking (also see, e.g., Kahn and

Kenney 1999, 75-76; Lau and Pomper 2004, 31-32). Challenger strategies have less certain, higher vari ance outcomes. For example, going negative?which

2 The behavior of open seat candidates likely depends on other fac tors (see Jacobson 2004, 98-99), including the candidate's ability to tie himself or herself to the incumbent, district partisanship, and the candidate's standing in the race. We will later explore some of these dynamics.

344

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

challengers do to stimulate attention?entails some risk; many voters disdain negativity (Geer 2006, 1-2;

Mark 2006) and its effect remains "uncertain" (Lau and Pomper 2004, 74). Similarly, utilizing interactive

Web technologies introduces substantial risk because candidates lose message control, with users choos ing what to view (Chadwick 2006, 8; Eveland and

Dunwoody 2002). Risk dynamics also exist with the content of mes

sages. Incumbents emphasize qualities?experience, familiarity, and district benefits?that most voters fa vor, and that very likely benefit incumbents. Chal lengers, in contrast, highlight criteria that may or

may not advantage them. For example, offering pre cise issue positions may alienate some voters (Page 1978), providing endorsements can backfire (Lupia and

McCubbins 1998,60-61), and introducing personal fea tures may, in the end, favor the incumbent (e.g., dis cussing leadership). Similarly, partisan emphasis could sway, alienate, or have no effect on leaners, whereas emphasizing partisan-owned issues could shape vote preferences, have no impact, or even deter voters who care about other issues (such as leaners or voters from the other party). In sum, risk constitutes a latent fac tor that links our predictions?challengers who must overcome the incumbency hurdle engage in signifi cantly more risky behavior. This portrayal coheres with

McDermott, Fowler, and Smirnov's (2008, 346) evo lutionary theory of decision making that posits that "when political... survival is threatened, [politicians] appear much more likely to engage in risky actions...." It also provides a generalizable portrait of behavior, one that we will empirically explore in what follows.

USING CANDIDATE WEB SITES TO STUDY CAMPAIGN STRATEGY

A central challenge for work on campaigns concerns the identification of an appropriate source of data. Lau and Pomper (2004, 133-34) explain, "Campaigns are not simple, in practice or analysis ... data?in partic ular, on the nature of the campaign itself?are much harder to come by" (also see Lipinski 2004, 9; Simon 2002, 94). Ideally, the data should be unmediated (i.e., directly from the campaign), complete (i.e., covering a full range of rhetorical strategies), and representative of the population of campaigns. We submit that candidate campaign Web sites

uniquely meet these criteria. First, Web sites are un mediated. Even when a campaign hires a consulting firm to help construct its Web site, it is the cam paign that determines the site's content (Ireland and Nash 2001, 60-61). This contrasts with news media coverage of campaigns (e.g., newspapers), on which some prior work relies (e.g., Lau and Pomper 2004; Sigelman and Buell 2003). Lipinski (2004,10) explains, candidates' "abilities to communicate through the mass media vary significantly [depending on] relations with local journalists_Therefore any analysis of media coverage will not provide an accurate measure of the messages that [candidates] are attempting to communi cate. Because of the problems associated with studying

mediated communication, it is essential to examine di rect methods_"

Second, Web sites offer as holistic or complete a portrait of campaign strategy as is available. A "campaign goes well beyond its televised politi cal advertisements_ Candidates engage in many activities?they give speeches, conduct rallies, dis tribute literature, and meet with local opinion leaders, editors, and other elites to seek endorsements (Shaw 1999)_To examine the effects of the campaign more broadly, we need a more comprehensive view beyond political advertisements" (Lau and Pomper 2004,134). On their Web sites, campaigns can post copious infor mation, including copies of advertisements, speeches, or other material (Ireland and Nash 2001, 60-61). As a result, a campaign Web site potentially captures the aggregation of campaign communications that reflect a campaign's overall rhetorical strategy. This differs from speeches or television advertisements that require can didates to choose brief snippets of their overall mes sage; candidates cannot possibly incorporate the full range of their rhetorical strategies (e.g., references to endorsements, polls, various issues, personal features).3

Third, virtually all congressional campaigns launch Web sites, which are critical for capturing a repre sentative sample of the population of congressional campaigns. In contrast, many House candidates and some noncompetitive Senate candidates fail to pro duce television advertisements (Goldstein and Rivlin 2005,16; Kahn and Kenney 1999,34).4 Similarly, major newspapers spend little time covering House races and noncompetitive Senate races. As a result, studies that rely on advertisements or media coverage use biased samples that often exclude House campaigns and less competitive (or less well-funded) Senate races. In the next section, we empirically demonstrate just how bi ased advertisement and newspaper coverage is, relative to Web sites.5

To assess the validity of our claim that Web sites capture the aggregation of campaign communication aimed at voters in general (e.g., the median voter), we conducted a survey of individuals involved in the design of congressional campaign Web sites during the 2008 campaign (N= 137). We provide details of the survey in Appendix A. Here we focus on the most telling results, many of which are consistent with what Stromer-Galley et al. (2003) report from a similar survey in 2002-3. We asked site designers to rate the priority of sev

eral groups of voters as Web site target audiences;

3 Indicative of the limitations of using television advertisements to capture the range of rhetorical campaign strategy is that the Wis consin Advertising Project (http://wiscadproject.wisc.edu/; accessed January 2009) does not code for many of the rhetorical features that are evident on Web sites.

4 We base this claim on what is available from the Wisconsin Adver

tising Project.

5 We do not mean to minimize the importance of studying televi sion advertisements and media coverage, particularly for research focused on the effects of mass communication on voters. Rather, our

point concerns using these media as unbiased measures of overall campaign strategy.

345

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

FIGURE 1. Web Site Visitor Priority and Visit Frequency

? ^ 5g ?~ c

1 *St 4 ?? 2 tt 3 o a*

?< 2

621 6.10 <115> (1.24)

I I "339" (1.68) 4.98 5.02

(2.18) (1.55)

H 1 ii

4 95 4.89 , (1-74) (1.56)

4.80 4.78

Voters In general Undecided voters Journalists

I Priority Visit frequency

Highly engaged Supportive voters voters

Group

Supportive activists

Bloggers

I N for priority ? 124; N for visits ? 114

we measured this on a seven-point scale with higher scores indicating increased priority. Respondents also rated their perception of how often an average mem ber of each group visited the site, on a seven-point scale with higher scores indicating more frequent vis its. The results, which we present in Figure 1, show that those involved in the creation of the sites view "voters in general" and "undecided voters" as the pri

mary target audiences. These two groups register signif icantly higher priority scores than all other groups (e.g., comparing "undecided voters" to "journalists," gives im = 3.86, p < .01 for a two-tailed test). This matches Stromer-Galley et al.'s (2003) aforementioned survey, which also finds that "undecided voters" were the top rated audience.

Interestingly, the respondents also recognize that "voters in general" and "undecided voters" visit less frequently than all other groups. Instead, they believe "highly engaged voters" access the site most often (also see Democracy Online Project 1999), even though these voters are not the primary target of the site (e.g., comparing the frequency question for "highly engaged voters" to "undecided voters" gives t\n = 8.97, p < .01 for a two-tailed test). This accentuates the importance of not confounding the frequency with which particu lar voters visit Web sites with the intentions of those

designing the sites (e.g., certain groups may be more important even if they visit less often) (cf. Trent and Friedenberg 2008, 402-4). And it is the intent of the designers that is critical to us, as a window into cam

paign strategy.6 In Appendix A, we describe additional survey results that also strongly suggest that Web sites are aimed at general voters (e.g., the designers view

Web sites as more representative of the "entire cam paign" than any other form of communication).

For a final piece of confirmatory evidence, we com pared the tone of the rhetoric (i.e., negativity) on Web sites with that found in television advertise ments and newspaper coverage. Although these lat ter two media contain limited and mediated con tent, respectively, we expect the general tone of the campaign?that is, negativity?to be correlated across media (e.g., although television advertisements cannot contain nearly the range of messages found on a Web site, they can be classified as negative in general tone or not). We report details, including the results, in Appendix B. The main point is that we find significant correlation in general tone across these communication channels, suggesting that Web sites capture the general rhetorical thrust of the campaign, while providing a near limitless opportunity for a campaign to directly include any information it deems relevant. All of this evidence supports the claim that Web

sites offer a valid measure of campaign strategy; they provide an unmediated, holistic, and representative

6 The importance of "journalists" is interesting because they often visit a site to obtain information that they then use in writing stories that reach broad audiences (e.g., Bimber and Davis 2003, 68-72; Semiatin 2005,166-67).

346

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

portrait of messages aimed at voters in general. We now turn to a description of our data collection and approach to measurement.

WEB SITE DATA COLLECTION

Our Web site data cover three election cycles, starting in 2002, a year in which Web sites first became "a crit ical part of any candidate's strategy" (Chinni 2002,1). In each year-2002, 2004, and 2006-we identified the universe of major party (Democrat and Republican) House and Senate candidates using the National Jour nal, Congressional Quarterly, and various state party home pages.7 We included the universe of Senate candi dates and then selected a systematic random sample of approximately 20% of House races, stratified by state and district to ensure regional diversity in the sample.

We searched for all of the Web sites in our sample by following links from the National Journal's Web site (www.nationaljournal.com) and using search en gines such as Google (www.google.com). We carefully identified candidates' personal campaign Web sites, ex cluding official congressional Web sites and Web sites sponsored by other groups or individuals. We successfully identified nearly all Senate candi

date Web sites and more than 95% of House sites in our sample. The few cases where the candidates did not launch Web sites came largely from earlier year races

where the candidates had no or very weak (e.g., inexpe rienced, low-funded) opponents. Our sample consisted of a total of 736 Web sites, with 26% coming from the Senate and 74% coming from the House.8 Not surprisingly?given our sampling approach?our sites accurately reflect the universe of campaigns, albeit with a slight overrepresentation of competitive races.9

To evaluate the biasness of other approaches, we identified the candidates in our sample who pro duced advertisements in 2002 and 2004 (relying on the

Wisconsin Advertising Project, which is fully avail

7 We also included independent Bernard Sanders of Vermont, who was a 2002 House incumbent and 2006 open seat Senate candidate, as well as incumbent Democrat turned independent Joe Lieberman in 2006.

8 The list of all sites coded is available from the authors. The only other study of candidate Web sites that approaches the breadth of our data is Foot and Schneider (2006). However, their focus significantly differs from ours.

9 Since we take a near census of Senate campaigns (e.g., exclud ing only the few candidates who did not have sites), this part of our sample almost perfectly matches the population in terms of incumbency and competitiveness. Our House sample contains 46% incumbents, 43% challengers, and 12% open seat candidates, which

mimics the respective population totals of 49%, 40.5%, and 10.5%. In terms of competitiveness?according to Cook's nonpartisan ratings (www.cookpolitical.com)?our House sample ended up slightly over representing toss-up campaigns, with 9% being toss-up, 18% being leaning or likely, and 73% being solidly in favor of one candidate, compared to respective population figures of 5 %, 14 %, and 81 %. The small overrepresentation of competitive races stems, in part, from our regional stratification, which inadvertently resulted in multiple races from some states with relatively few congressional districts that happen to regularly be competitive (e.g., New Mexico). It also stems slightly from our retaining some districts in our sample in each election cycle in order to allow researchers to follow candidates over time.

TABLE 1. Candidates Lacking Television Advertisements and News Coverage, 2002-2004

Toss-up

Likely or leaning

Solid

Incumbents

Challengers

Open seats

% with no TV Ads

21.28% (10/47) 9.47% (9/95)

63.91% (193/302) 47.94% (93/194) 56.83% (104/183) 21.21% (14/66)

% from races with fewer than 16

articles

16.22% (6/37)

26.19% (22/84) 55.26%

(147/266) 52.12% (86/165) 46.50% (73/157) 25.00% (16/64)

able only for these years10) and who received cov erage in major newspapers in these same years. For the newspapers, we identified relevant newspapers and then searched for pertinent campaign articles that

mentioned either candidate (from Labor Day until Election Day) (Lau and Pomper 2004; Sigelman and Buell 2003).11 We identified campaigns for which there were at least 16 articles, in accordance with Lau and Pomper's (2004, 135) minimal standard for capturing campaign content. The total possible number of can didates producing television advertisements is 444, be cause that is the number in our sample for 2002-4; for the newspaper articles, the maximum number is 387, because we failed to identify electronically available newspapers from eight races.12 We find that nearly half of our sample would be

missing if we relied on television advertisements or newspaper articles. Specifically, 47.75% (212/444) of the campaigns in our sample did not produce even a single television advertisement, and 45.22% (175/387) participated in races that did not generate the minimal standard of 16 news articles. Moreover, samples relying on these data display systematic biases. Table 1 reports the percentage of candidates who did not produce an advertisement and failed to participate in a mini mally covered race, broken down by competitiveness (based on Cook's ratings; see note 9) and candidate sta tus. Clearly, a disproportionate number of candidates without advertisements or sufficient news coverage come from the least competitive (i.e., "solid") races? 64% and 55% of candidates from these races lack advertisements and sufficient news coverage, respec tively. Interestingly, however, a nontrivial number of

10 In 2006, the project only coded a small subset of campaigns in the Midwest.

11 The list of newspapers used is available from the authors (see also Kahn and Kenney 1999). 12 This includes races from Iowa, Connecticut, Delaware, Hawaii, Idaho, Kentucky, Mississippi, and South Dakota. We also have one

missing observation for the candidate status analyses; hence the total Ate of 443 and 386 for those data.

347

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

TABLE 2. Dependent Measures

Variable Measure Percentage/

mean (std. dev.)

Negativity Issue negativity3 Personal negativity3

Interactive^

Negative (critical) statement about opponent. Negative (critical) issue-oriented statement about opponent. Negative (critical) personal statement about opponent. Web Site allows for content or interpersonal interactive

47.95% 43.91% 30.11% 29.08%

Issue ownership

Positions Endorsements

Weighted relative partisan advantage of issues discussed (average, based on annual public opinion measures). (The range is -20 to 26, with negative scores being the inverse of ownership and 0 being neutral.)

Number of unambiguous issue positions taken (0-4). Number of nonpartisan official endorsements provided (0-100).

1.77(9.55)

1.83 (.97) 11.82(20.40)

Leadership

Competence

Empathy Pollsa

Statement about why the candidate is running for office (e.g., discussion of leading in a certain direction).

Statement about prior occupations and experiences relevant to holding office.

Details about family. Inclusion of a poll result.

34.65%

82.20%

46.52% 15.54%

Party emphasis Party highlighted on front

?lfai?fll 8.56%

Prior office experience Familiarity District benefits

Statement about holding prior elected public office. 66.17% Statement about growing up in or being from the state/district. 61.82% Number of statements (0-4) about an action taken to address an 0.86 (1.03)

issue or promote a policy (that may benefit constituents).

1 Data collected only in 2004 and 2006.

candidates from even the most competitive races would be absent from a data set relying on advertisements or news coverage (21% and 16%, respectively). The bottom part of the table shows that only 21% and 25% of open seat candidates lack advertisements or cov erage, compared to roughly 50% of incumbents and challengers; this suggests a relative overrepresentation of open seat candidates.13 These results further accen tuate the advantages of using Web sites to measure campaign strategy?unlike other approaches, we can generalize beyond highly competitive races and include a representative sample of House, and not just Senate campaigns.

Web Site Measures

To analyze the Web sites each year, we assembled teams of student coders. All coders participated in a de tailed training session before being randomly assigned

13 In analyses available from the authors, we find that competitive ness and challenger status significantly determine whether or not a candidate produces an advertisement (also see Franz et al. 2008,57). The same is true for newspaper coverage. These biases are evident in strict comparisons with the population of campaigns (as opposed to comparisons with our Web site sample, which, as mentioned, slightly overrepresents competitive races). In other words, our minimal bias toward competitive races comes nowhere near the extent of the bias in newspaper coverage and television advertisements.

sets of candidate Web sites. We conducted all coding in the 10 days preceding Election Day. However, we also tracked a small sample of Web sites from after Labor Day until Election Day and found little evidence of changes that would have significantly altered our coding (i.e., changes usually concerned items such as the candidate's schedule). For the years in our sample, we thus believe that our coding approach successfully captured campaign strategy.

To measure our dependent variables, coders exam ined the front page, the page(s) devoted to fundraising, the page(s) devoted to issues, the page(s) devoted to biographical information, and any other "major" page (e.g., with a link from the front page; this included news room and media pages). In practice, this amounted to coding the entire self-contained site (coders did not fol low links to other Web sites). We describe our specific variables for each hypothesis in Table 2,

Our first prediction states that, compared to in cumbents, challengers will go negative more often and provide more opportunities for voters to en gage with the campaign. We measure the latter con cept by distinguishing Web sites that allow some form of interaction?regarding content or interper sonal communication?from those that do not. To

14 Specifically, we coded whether sites allow users to person alize information, arrange information, add information, and/or

348

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

measure negativity, we follow Geer's (2006, 23) de piction of it as "any criticism leveled by one candidate against another during a campaign" (also see Buell and Sigelman 2008). We used a dichotomous variable indi cating whether a candidate included material on the site that was negative or critical of his or her opponent (in tone or explicitly). We opted for a dichotomous

measure, rather than a count across the entire Web site, for two reasons. First, on a particular page, we found it difficult to reliably count the number of neg ative statements (when does a negative statement end and another one begin?). Second, using a subsample of 41 sites, we counted the number of distinct pages (e.g., the front page, personal page, issue page) that included negativity. We found very little variance, such that most candidates who went negative on their sites did so twice (most typically, on the front page and issues page). Not surprisingly, then, we find virtually identical results when using this count or employing our simpler and more reliable dichotomous indicator across the entire site.15

In 2004 and 2006, we also coded each site for whether the negativity focused exclusively on issues (e.g., "my opponent has a bad record on taxes"), exclusively on the person (e.g., "my opponent is not trustworthy"), or on both issues and the person (e.g., Geer 2006; Kahn and Kenney 1999; Lau and Pomper 2004). These dis tinctions enable us to assess whether our prediction holds across types of negativity.

Operationalizing our second hypothesis requires measuring the aforementioned issue, personal features, and partisan variables. To capture candidate emphasis on advantageous issues, we build on issue ownership theory, which suggests that candidates benefit from highlighting issues on which their party is preferred (e.g., a focus on the environment favors Democrats whereas a focus on homeland security favors Repub licans). We collected data from multiple polls on the public's perception of which party owned a host of policy issues (Hayes 2005, 910; Petrocik 1996, 832).16 We then computed, for each candidate, the weighted partisan advantage (according to public opinion) of the issues emphasized on their front page, biography page, and/or issues page.17 The scores range from -20 to 26, with positive numbers indicating increased ownership

communicate with other voters and/or the candidate (e.g., interactive posts to a blog) (see Druckman, Kifer, and Parkin 2007). 15 In our subsample, the average number of negative statements across the Web site is 2.07, with a standard deviation of 0.46.

16 Sources for this data came from a search of the iPoll databank pro

vided by the Roper Center for Public Opinion Research, University of Connecticut. Further details are available from the authors.

17 For each issue, in each individual year, we average the party's advantage/disadvantage and assign points to the candidates based on the number of times that each issue is emphasized on their front pages, biography pages, and/or issues pages. For example, a Demo cratic candidate in 2002 would get 22.9 points for every time he or she mentioned the environment because the Democrats enjoyed a 22.9% public opinion point advantage over Republicans on this issue in 2002. The same Democratic candidate would lose 16 points; however, for every time he or she mentioned homeland security, because the Republicans held the public's confidence by 16 points on that issue in 2002. We then divided the sum by the total number of

of the emphasized issues by the candidate's party and negative scores the inverse. We operationalize position taking by summing the number of unambiguous issue positions (where a counter position is easily identified) offered by the candidate on the front page or issues part of the site (up to four, which captures most variation among candidates). We also counted the number of official endorsements (e.g., from the AFL-CIO, farmer groups, teachers, Right to Life, NRA, NOW, Sierra Club) anywhere on the site (up to 100).18

Previous research offers less guidance on how to re liably measure personal feature rhetoric, leading us to develop plausible proxies. For leadership, we coded whether the candidate included a statement (on the front page or biography pages) explaining why he or she was running for office. These statements invariably invoke the desire to make a difference and help lead in a certain direction. For competence, we coded for dis cussion of prior relevant occupations and experiences.

We measured empathy with whether the candidate of fered details of his or her family. Although this last variable is fairly indirect, we suspect that candidates include this type of information in the hope of portray ing themselves as "down to earth" people who are in touch with the concerns of typical families. We coded

whether a candidate included poll data, which in every case demonstrated the candidate's good standing in the race. (We did not collect poll data in 2002.)19 Finally, for party emphasis, we measured whether the candidate highlighted his or her party on the front page (i.e., in the banner at the top of the front page).

To test our incumbency hypothesis, we measured the three aforementioned incumbency features?expe rience in office, familiarity, and the provision of district or state benefits (which we hereafter call "district bene fits") (Jacobson 2004). We used dichotomous measures to indicate whether the candidate discussed, on the front page or biography pages, having held any public office and whether he or she accentuated ties to the district/state by mentioning having grown up or lived much of his or her life in the area (thereby displaying fa miliarity). To measure district benefits, we summed (up to four) the number of candidate statements about an action taken that potentially benefited the constituents; examples include obtaining something for the district, organizing events or introducing legislation concern ing a local issue, and meeting or working with other politicians to discuss a locally relevant issue.

To assess coding reliability, we randomly sampled approximately 30% of the Web sites and had one of two reliability coders code these sites. Specific reliabil ity statistics are available from the authors; for all the

issues mentioned by the candidate. These scores enable us to explore variation in issue ownership?that is, which candidates engaged in more or less ownership (cf. Dolan 2005; Sellers 1998; Sides 2006; Sulkin and Evans 2006). 18 These endorsements nearly always came from issue-oriented groups, with the only notable exception being newspapers.

19 As with negativity, we coded a small sample of sites to assess any changes in our results if we instead counted the number of polls referenced across the site. We found no change whatsoever using this variable.

349

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

variables used in the analyses below, we find high levels of reliability, nearly always exceeding the .80 threshold, correcting for chance agreement (Neuendorf 2002,143; Riffe, Lacy, and Fico 1998,131).

RESULTS

Our hypotheses involve two key explanatory variables: candidate status and competition. We use dichotomous variables to distinguish challengers, incumbents, and open seat candidates. As mentioned, for competitive ness, we use Cook's ratings to classify races as 0 = solid Democratic or Republican, .33 = likely Democratic or Republican, .67 = leaning Democratic or Republican, or 1 = toss-up. Scholars commonly rely on Cook scores because they have the virtue of being exogenous to the races themselves (e.g., Goldstein and Freedman 2002; Gronke 2000,100-101; Sulkin 2001).20

Candidate status and competitiveness correlate with a number of other variables shown to affect campaign behavior. Testing our hypotheses, therefore, requires the inclusion of control variables including year, office (Senate or House), party, gender, funds raised, front runner status, and district/state partisanship. Moreover, a few of our particular measures require additional controls, such as the holding of any prior office for the incumbency measures (e.g., challengers who never held prior office cannot talk about their experiences doing so) and issue salience for the issue ownership measure (e.g., candidates might emphasize salient issues). We describe all of the control measures in Appendix C.

We test our first three hypotheses by regressing each dependent variable on candidate status, competition, and the controls. We display the regressions in Ap pendix D, where interested readers can assess the im pact of the control variables. We focus here on the impact of candidate status across the dependent mea sures. Specifically, we use regressions akin to those in Appendix D to generate the predicted probability that an average challenger will engage in a given be havior and the predicted probability that an average incumbent will do so.21 (For interval-level dependent variables, we focus?for presentational reasons?on the probability of being above the mean value, such as citing more than the mean number of district benefits.)

We set all other variables to their mean values.

We present the results in Figure 2. They show that, in every case, there are statistically significant and sub stantively meaningful differences between challengers and incumbents. For example, the probability of the average challenger going negative is .65, which is dra matically higher than the incumbent likelihood of .31 (also see Druckman, Kifer, and Parkman n.d.). This same dynamic holds for both issue and personal nega tivity. It also occurs with Web site interactivity, with the likelihood of an average challenger employing

20 In Table 1, we collapsed the two middle categories for presen tational purposes; unless otherwise noted, we do not do so in our analyses. 21 We compute all probabilities presented in the paper using Clarify (Tomz, Wittenberg, and King 1999).

some form of interactivity being .32, compared to .24 for the average incumbent. Even more impressively, challengers exhibit significantly greater likelihood of emphasizing every issue, personal feature, and party measure. It is striking, then, that the probabilities com pletely shift when it comes to the incumbency behav ior of prior office experience, familiarity, and district benefits. The substantive differences range from .40 in the case of issue negativity to .10 in the case of party emphasis. Across all behaviors, the average difference probability for engaging in a behavior is .18 (std. dev. .09). This means that, all else constant, incumbents and challengers differ in their likelihood of employ ing different rhetorical strategies by 18% on average.

The results not only constitute the first empirical con firmation for many of the individual measures (e.g., even the issue ownership literature had yet to explore variance in claims of ownership), but also, when taken together, reveal fundamental alternative approaches to campaigning.22 We test our next hypothesis?that incumbents place

greater relative emphasis on incumbency factors as the race becomes increasingly competitive?by adding in teractions between competitiveness and the candidate status variables to the incumbency regressions (again available in Appendix D). We then generate relative probabilities (i.e., incumbency probability - challenger probability) of engaging in each type of incumbency strategy for noncompetitive (solid), moderately com petitive (likely/leaning), and highly competitive (toss up) races.23 We display the results in Figure 3, with the asterisks indicating significant differences between incumbents and challengers for the given competi tiveness level. As expected, incumbents differ signif icantly from challengers in their likelihood of empha sizing aspects of incumbency only as the race becomes more competitive. For example, in the least competi tive races, incumbents do not place significantly more emphasis than challengers on any of the variables; in fact, they put less weight on prior office and district ben efits (although the differences are not significant). In contrast, in the most competitive races, we see that the incumbents are respectively 52%, 28%, and 16% more likely to highlight district benefits, familiarity, and prior

office than challengers (all significant differences). We also coded for whether the candidate provided

a campaign event schedule on his or her Web site. Consistent with the results, just reported, we find the relative likelihood of incumbents posting a schedule increases as the race becomes more competitive (i.e., in less competitive races, they are less likely to actively campaign). Specifically, incumbents are approximately 18% less likely than challengers to post a schedule in

22 Our results are not being driven by a particular chamber; when we add interactions between candidate status and chamber (e.g., Senate), the challenger variable remains significant, in ail analyses, for both chambers (also see Gronke 2000). We will later explore chamber differences in more detail.

23 For presentational purposes, in Figure 3, we merge likely and leaning into one category. The results are robust if we break these out, although there are no significant shifts, in the expected direction, between likely and leaning races.

350

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

FIGURE 2. Candidate Status and Campaign Content

Challenger Incumbent

Content

**AII challenger-incumbent probabilities

significantly differ at p ? .05, one-tailed

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

FIGURE 3. Relative Probability of Incumbent Behavior

Si5 E m?? I I* ?

o c?

Solid Likely/leaning Toss-up

Prior office -Familiarity ' District benefits

Competitiveness

|***p$ .01; **p< .05; *p<? .1, one-tailed|

noncompetitive and leaning/likely races, but only 10% less likely in the competitive races (which is a signif icant change)^ These incumbency results support the notion that incumbents operate in two distinct politi cal universes, depending on the competitive nature of the race. Importantly, when we explore interactions between competitiveness and candidate status for the other (challenger) behaviors, we find significance in only two cases (i.e., negativity and issue ownership).24 This suggests that, unlike incumbents, challengers' strategies do not substantially change based on competitiveness.

Challengers as Risk Takers25

We previously explained that risk-taking constitutes a latent factor distinguishing challengers' and incum bents' strategies. Challengers employ tactics with un certain consequences (e.g., will negativity alienate? will partisanship resonate?) whereas incumbents enjoy more certainty (e.g., nearly all voters prefer district ties, benefits, office experience). We operationalize this ar gument by aggregating the strategies we have explored

24 We find that the relative probability of challengers (as opposed to incumbents) going negative shrinks as races become more compet itive, and that the relative probability of challengers (as opposed to incumbents) engaging in issue ownership increases with competition.

25 We thank the APSR's editors for suggesting the analyses and dis cussion contained in this section.

into a single risk-taking measure. For each candidate, we summed the number of risky ("challenger") strate gies, and from that sum, subtracted the use of any of the safe ("incumbent") strategies.26 (We exclude issue and personal negativity as well as polling because we do not have data on these variables for 2002.) The result is a count variable ranging from ?3 to 8, with higher scores indicating an increased tendency toward risk. The average is 2.28 (std dev. 2.15). In Table 3, we present results from regressing the measure on the key explanatory factors (see Appendix C for details on the independent variables).27 The first column of Table 3 confirms our central

prediction?challengers engage in significantly more risky behavior than incumbents. Substantively, the average challenger undertakes 3.32 (standard error: 0.13) risky behaviors, whereas the average incum bent employs 1.23 (0.13).28 The results also reveal the

26 As we did in generating Figure 2, we transform ordinal/interval level variables based on falling below or above the mean. This allows us to create an aggregate measure that gives equal weight to each strategy (which, although debatable, is agnostic). We exclude candi dates who had missing data on any one of the strategies in the risk index.

27 The sample size drops because of missing fund raising data and missing data on our issue ownership variable (i.e., we did not compute issue ownership scores for candidates who failed to mention an issue for which we had commensurate public opinion data). 28 To compute these values, we treat our risk index as interval level and use Clarify, setting all other variables to their mean values.

352

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

TABLE 3. Risk-Taking

All data House data Senate data All data

Challenger

Open seat

Competition

2004

2006

Senate

Democrat

Female

Funds raised

Front-runner status

District Republican

Open X front-runner status

Challenger x front-runner status

Log likelihoodN

1.37***

(0.15) 0.77*** (0.14) 0.26** (0.12) 0.18** (0.11) 0.31*** (0.10)

-0.15* (0.11) 0.95*** (0.08) 0.07 (0.11) 1.52***

(0.60) -0.51***

(0.15) 0.002 (0.004)

-1265.12 692

1.40***

(0.19) 0.74*** (0.17) 0.46*** (0.18) 0.06 (0.13) 0.18* (0.12)

0.96*** (0.10) 0.09 (0.12) 1.96 (2.65)

-0.59*** (0.19) 0.004 (0.004)

-917.52 509

1.34**

(0.27) 0.93** (0.26)

-0.10 (0.22) 0.37** (0.19) 0.53** (0.20)

1.04***

(0.17) -0.06

(0.21) 1.32**

(0.70) -0.33

(0.27) -0.014*

(0.010)

-333.46 183

1.78***

(0.29) 1.32***

(0.30) 0.35*** (0.15) 0.17** (0.11) 0.31*** (0.10)

-0.17* (0.11) 0.95*** (0.08) 0.08 (0.11) 1.66***

(0.61) -0.06

(0.29) 0.002 (0.004)

-0.84** (0.40)

-0.54 (0.47)

-1262.92 692

Note: The dependent variable is our index of risk-taking behavior, ranging from -3 to 8. Entries are ordered probit coefficients with standard errors in parentheses. ***p < .01 ; **p < .05; *p < .10 for one-tailed tests. The coefficients and standard errors for x\ through r-n are as follows (reading across the table): for model 1, -2.21 (0.33), -1.45 (0.28), -0.55 (0.26), 0.16 (0.25), 0.87 (0.25), 1.48 (0.26), 2.17 (0.26), 2.69 (0.27), 3.37 (0.28), 4.03 (0.30), 4.77 (0.35); for model 2, -2.14 (0.36), -1.43 (0.32), -0.58 (0.30), 0.10 (0.30), 0.82 (0.29), 1.53 (0.30), 2.20 (0.30), 2.72 (0.31), 3.45 (0.33), 4.11 (0.35), 5.00 (0.43); for model 3, -2.35 (0.70), -1.10 (0.62), -0.28 (0.61), 0.43 (0.61), 0.83 (0.61), 1.57 (0.62), 2.14 (0.63), 2.74 (0.64), 3.41 (0.66), 3.93 (0.71); for model 4, -1.78 (0.41), -1.03 (0.37), -0.12 (0.36), 0.58 (0.36), 1.29, (0.36), 1.91 (0.36), 2.60 (0.36), 3.12 (0.37), 3.81 (0.38), 4.47 (0.39), 5.21 (0.43).

importance of competition, with the significance both of our competition variable and of the funds raised measure (e.g., fund raising increases in close races). Not surprisingly, front-runners avoid risk?they have no need to take chances. Risky behavior also increases with open seat candidates and Democrats (who were largely the minority party for these years) and over time. Perhaps most interesting is the (marginally) sig nificant negative Senate effect. The average Senate candidate engages in 2.09 (0.14) risky behaviors, com pared to 2.33 (0.07) for the House. Senate candidates, particularly in competitive races, may put more empha sis on less risky incumbency factors, in light of recent trends of a greater Senate incumbency advantage (An solabehere and Snyder 2002, 320).29 In the next two columns of Table 3, we probe chamber differences fur ther by presenting regressions separately for the House and the Senate. Although the results reveal some dis

29 Ansolabehere and Snyder (2002,320) show that from 1992 to 2000 the Senate incumbency advantage exceeded the House's by 2.77%.

tinctions, the challenger-incumbent difference is ro bust, and in fact virtually identical across chambers.30 It thus appears that chamber variation in risky behavior applies across candidates (and not just to incumbents or challengers).

The final regression in Table 3 explores a dynamic about which we have thus far said little?the behav ior of open seat candidates. Our approach suggests that front-running open seat candidates may act like incumbents. These candidates, who in practice almost always come from the prior incumbent's party,31 do not need to overcome an incumbency advantage, and their front-runner status means they have little incen tive to take risks. We test this by adding an interac tion between open seat status and front-runner status

30 We posit that the differential chamber effects of competition and funds raised reflect funds being a more precise measure of compe tition in the Senate, due to much greater variance in Senate funds raised.

31 For example, 78% of open seat candidates who fall into our highest front-runner category come from the party of the prior incumbent.

353

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

FIGURE 4. Party Emphasis

District-level incumbent partisanship

?Challenger?a? Incumbent

with the expectation of a significant negative coefficient (which would indicate a smaller open seat main effect).

We add an analogous interaction between challengers and front-runner status, although we do not expect it to be significant. Even front-running challengers need to take steps to overcome the incumbency advantage (and thus we do not expect the challenger main ef fect to diminish, as would be indicated by a signifi cant negative interaction). The results support these expectations; the open seat-front-runner interaction is highly significant and the challenger interaction is not.32 The significant negative interaction shows that the open seat main effect dramatically shrinks for front runners; the average front-running open seat candidate engages in 1.67 (0.27) risk behaviors compared to 3.02 (0.26) for the average trailing open seat candidate. These predicted means nicely match the aforemen tioned respective challenger and incumbent means of 1.23 and 3.32.33

To gauge just how much risk challengers are will ing to take, we now further explore partisan strate gies. Emphasizing one's party and/or engaging in issue ownership (i.e., focusing on issues of particular impor

32 Twice the difference in log likelihoods is distributed as chi-square with the difference in the number of parameters as the degrees of freedom. Thus the first model in the table compared to the final one

gives Prob(x22 > 4.4) = .11. If we only include the open seat-front runner interaction, the chi-squared probability becomes .08.

33 When we run this regression separately for the House and Senate, we find the interaction is only significant for the House, possibly reflecting the aforementioned perception of a smaller incumbency advantage in the Senate.

tance to fellow partisans) become increasingly risky as the number of fellow partisans in the district/state decreases (e.g., highlighting Democratic party status is risky when there are fewer Democratic voters). In Figures 4 and 5, we plot the extent to which incumbents and challengers, on average, emphasize partisanship and engage in issue ownership (i.e., on a standardized scale where 0% indicates equal attention to owned and unowned issues and 100% equals maximum attention to owned issues).34 The jc-axis displays the percentage of the district or state that shares the incumbent's parti sanship, as indicated by the standard presidential vote in the district or state measure (Carson, Engstrom, and Roberts 2006). Both figures show that, as revealed in Figure 2, challengers employ these strategies signifi cantly more often, and that the candidates sensibly re spond to district partisanship?for example, challengers become less likely to use partisan tactics when more of their constituency consists of members of the opposing party.

More important are the regions where a majority of the constituency voted for the presidential candidate of the incumbent's party (e.g., suggesting that the me dian voter is of the incumbent's party or perhaps an

34 Recall that the issue ownership variable ranges from -20 to 26 (where negative numbers indicate putting more emphasis on issues owned by the other party). We computed predicted scores for chal lengers and incumbents on this scale. We then standardized them by dividing the predicted scores by the empirical maximum of owner ship (in our sample). By so doing, we ignore the possibility of nega tive scores; however, including this possibility in our standardization leaves the displayed trends unchanged.

354

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

FIGURE 5. Issue Ownership

25%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% District-level incumbent partisanship

? ?Challenger?a? Incumbent I

Independent), but challengers, nonetheless, continue to employ partisan approaches more than incumbents. That is, challengers put relatively more emphasis on aspects of their party despite the fact that the majority of their potential constituents are, at the very least, not strong supporters of their party. This accentuates the tremendous extent to which incumbents avoid un

certainty using incumbency-focused messages "devoid of partisan or even programmatic content" (Jacobson 1992,141). It also reflects the small choice challengers have other than to employ strategies whose ultimate outcomes are uncertain at best (perhaps reflecting some desperation).

Negativity and Content

Our portrayal of risk as the underlying latent factor be hind incumbent and challenger strategies suggests a co herence to these strategies?that is, candidates' strate gies entail more than a patchwork of various points of emphasis. Consistent with this argument, we expect a connection between the type of negativity (used to stimulate attention) and the content of a candidate's message.

As discussed, a candidate can go negative by attack ing the opponent on issues, personal features, or both (e.g., Geer 2006). If, as we have argued, candidates go negative to motivate voters to attend to rhetoric that shifts the criteria of choice, then it is sensible that the type of negativity employed would cohere with the criteria the candidate emphasizes. Candidates who go negative on issues are likely to emphasize issues more than those who do not go negative on issues; candidates

who go personally negative are likely to emphasize personal features more than those who do not go per sonally negative.35 Extant work has yet to explore this possibility, instead treating negativity as an end in itself, rather than as part of a larger rhetorical strategy aimed at altering the criteria of electoral choice. We test this by adding two variables?indicating

whether the candidate went personally negative and whether the candidate went negative on issues?to the same regressions that generated the probabili ties reported in Figure 2 (and that can be found in

Appendix D).36 We then compare the computed prob abilities of engaging in a given type of rhetoric for candidates who went personally negative against those for candidates who did not go personally negative. We do the same for issue negativity. (Candidates may have engaged in both types of negativity.)

Figure 6 reports the changes in probability for both personal and issue negativity.37 For example, the like lihood of emphasizing unambiguous issue positions

35 Our prediction is not that they will put relatively more emphasis on issues or personal features within their Web sites. Rather, we purport that they will pay greater attention to these criteria than will other candidates who do not go negative in the same way. It is. possible that a candidate might pursue both an issue and a personal feature strategy, in which case we would expect both issue and personal negativity.

36 Recall that our data on type of negativity are limited to 2004 and 2006. The regressions are available from the authors. 37 All other variables are again set at mean values (including the alternative type of negativity). We do not provide standard errors because the figure presents differences. Indications of statistical sig nificance in the figure reflect the significance of the given type of negativity in the regression that generated the probabilities.

355

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

FIGURE 6. Negativity Type and Campaign Content

.12+

.11***

.1**.1** .1***

1C

.07**

.05

COC

Z6 C

0 .02.0

Cd M

1.01

8o

-.03

-.05 - - 4 -

-.06*

AC

.1

Issu ownership Positions Endorse Leadership Competence Empathy Polls Partyemhss Porffe Faliit Dsrctbnis

Content

0 Personal negativity M Issue negativity **I.1* .5 .- .3oetie

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

increases by a significant 10% for candidates who go negative on issues (compared to those who do not). The results support our contention that negativity forms part of a larger campaign strategy aimed at inducing voters to base their decisions on issue and/or personal criteria. Indeed, the likelihood of engaging in each type of issue strategy?issue ownership, position-taking, and offering endorsements?significantly increases when a candidate goes negative on issues (ranging from 10% to 12% increases). Analogously, candidates who go personally negative display a significantly greater likelihood of emphasizing personal rhetoric, including leadership, competence, empathy, and polls (with the increased likelihood ranging from 7% to 10%). We find little evidence of a relationship between negativity and the incumbency-based rhetoric or party emphasis, which is not surprising, as we had no expectation of meaningful connections.

These results support our overall portrait of cam paign strategy. Challengers and incumbents fundamen tally differ in the criteria they emphasize, with chal lengers placing more emphasis on issues, personal fea tures, and party, and incumbents putting more relative weight on the factors that underlie incumbency. Chal lengers and incumbents also differ in terms of their re sponsiveness to competition. Whereas challengers are consistently willing to take risks, incumbents will only do so when races tighten. These distinct tactics cohere into comprehensive campaign strategies, which basi cally amount to challengers opting for riskier options. That candidates connect the content of their rhetoric

to its tone (i.e., type of negativity) constitutes further evidence that candidates carefully calibrate their entire strategies.

Advantages of Web Data We argued that an advantage of the Web data?in ad dition to their being unmediated and holistic?is their representativeness (e.g., see Table 1). To see how this can impact substantive conclusions, consider Lau and Pomper's (2004, 36) finding, based on Senate newspa per coverage from 1992 through 2002, that challengers do not significantly differ from incumbents in terms of the likelihood of going negative. This contradicts our finding (also see Kahn and Kenney 1999, 74-98). In addition to using alternative media and different years, it may be that their nonfinding stems from reliance on a sample that excludes noncompetitive races (and House races) and overrepresents open seat races (see Table 1). To test this possibility, we reran our basic negativity analysis (see Figure 2; Table D-l) on the subsample of all candidates for whom we could access newspaper articles and who met the 16-article mini mum used by Lau and Pomper (for 2002-4, the period for which we counted newspaper articles). We find that the challenger variable becomes insignificant (b = 0.15, se = 0.69, p < .45, for a one-tailed test).38 When we do an analogous analysis but just for campaigns that

38 To be fair, this likely stems in part from Lau and Pomper's (2004) 16-article minimum. When we use our own coding of Senate news

produced television advertisements in 2002 and 2004, we find that the challenger effect just falls short of significance (b = 0.61, se = 0.56, p < .15).39 Yet, if we analyze the full sample of our Web data for those same years, we continue to find significant challenger effects (6 = 0.82, se = 0.46,/? < .05). To evaluate the overall impact of limited television

and newspaper samples, we reran our basic analysis for each dependent variable using only the data that would be available based on accessible newspaper coverage with at least 16 articles, and only on the production of television advertisements. For newspapers, we find that we would have failed to find a significant challenger incumbent distinction for eight of the dependent vari ables explored in Figure 2: negativity, positions, lead ership, competence, polls, party emphasis, prior office, and familiarity. We would have failed to find significant effects with a sample akin to what would be avail able with television advertisements for six variables:

negativity, personal negativity, competence, polls, prior office, and familiarity.4" Clearly, the nature of the sam ple used to study campaign communications can have notable effects on the findings. Limited samples may obscure an important distinction in the way that in cumbents and challengers campaign.

CONCLUSION

Campaigns are critical to democracy and thus deserve significant scholarly attention. Extant research often proceeds in a piecemeal fashion, focusing on one strat egy at a time (e.g., negativity, issue ownership), and relies on less than ideal data. We have attempted to advance the study of campaigns by integrating past work and offering a new data source. In so doing, we brought together previously disparate literatures and incorporated a wide range of understudied campaign behaviors (e.g., the use of polls, personal feature em phasis). We also established the virtues of using Web data as an unmediated, holistic, and representative way to measure campaigns. As in other work, we find that challengers and incumbents behave differently, but un like prior work, we systematically explored these differ ences across campaign behaviors, recognized the con tingent nature of incumbent behavior (based on com petition), identified a potential underlying dynamic be hind strategic differences (i.e., risk-taking), and linked negativity to the content of candidates' rhetoric.

paper coverage from 2002 through 2006 (see Appendix B), we find significant challenger effects on negativity for all coding, but the sig nificance of the effect disappears (just barely) when we limit analyses to races that included a minimum of 16 articles.

39 We find a significant relationship if we exclude the independent variable of whether the opponent went negative. Also, when we run a basic model using the number of television attack advertisements produced as the dependent variable (only for those who produced ads), we find a barely significant effect. (We find a similar effect when we combine attack and contrast television advertisements as the dependent variable; see Franz et al. 2008). 40 When we use our full sample but only for 2002 and 2004 (i.e., the period for which we analyze the TV and newspaper data), we continue to find significant challenger effects for all variables except going personally negative.

357

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

Our results suggest a number of intriguing directions for future research. First is the question of whether our findings will hold over future years, as political condi tions continue to evolve. The extent and nature of the

incumbency advantage changed in the 1990s with the rise of nationalized elections, active parties, and issue oriented interest groups (Fiorina 2004; also see Koch 2008). Although it is unclear whether these changes affected campaign strategies, it seems likely that con ditions will continue to change in ways that may or may not impact strategies. Similarly, future work can iden tify when the same basic dynamics hold across commu nication channels, including television advertisements, news coverage, speeches, direct mail, and debates. Sec ond, the ultimate success of these alternative campaign strategies remains unclear. Do incumbents who em phasize aspects of incumbency fare better than those who do not? As the literature on the effects of cam paign spending (e.g., Gerber 2004) reveals, assessing these effects will not be straightforward. Third, we have left unanswered the question of why some challengers opt for an issue focus, whereas others emphasize per sonal features or party (or some mix). The sources of these choices likely lie in the nature of the candidate's constituency.

Fourth, we are struck by the similarity between our work and Groseclose's (2001) influential formal model. Groseclose examines a situation where one candidate has a potential valence advantage, such as incumbency. He shows that in an attempt to counter the valence/incumbency advantage, a challenger will take relatively extreme policy positions (i.e., diverge from the median). The challenger does this because it minimizes the salience of the valence advantage (see Groseclose 2001, 864-65). Similarly, we show that to counter a valence/incumbency advantage, challengers engage in risky strategies that alter the relative impor tance of different considerations. For us, candidates do this by explicitly priming alternative considerations. An intriguing direction for future research would be to further integrate our approaches; for example, one could extend Groseclose's model to incorporate alter native criteria of voter choice (e.g., disaggregate his valence term), add salience weights to the criteria, and allow candidates to choose between attempts to alter salience or engage in extreme position taking. Negativ ity also could potentially be brought into his model by allowing candidates to go negative and then with some probability cause voters to reconsider the basis of their vote choice. On the flip side, our approach could draw on Groseclose's and incorporate position-taking and a more explicit consideration of the opponent's position and strategy.41

41 We reran all of our analyses with an added variable indicating whether the opponent engaged in the given behavior (e.g., for the dependent variable of issue ownership, we included a measure of the opponent's issue ownership). Although we find that this variable is significant in several cases?indicating that the more likely the opponent engages in a given behavior, the more likely the candidate does?in no cases did it alter the main statistical or substantive results.

The challenge in interpreting these results is that it is unclear whether

Another literature with which more definitive con

nections should be made is work on political market ing and segmentation (e.g., Newman 1999, Newman and Perloff 2004, Palmer 2004). We focused on "on average" strategies, but candidates of course also fine tune parts of their messages for particular audiences, and we imagine will do so to a greater extent in the future (e.g., in our data, candidates do not seem to be taking full advantage of targeting opportunities, as indicated by the relatively few candidates who allow interactivity on their Web sites). Also, some of the

work on which we explicitly built?particularly Trent and Friedenberg (2008)?offers additional predictions about incumbent and challenger behavior that can be tested (e.g., challengers will emphasize traditional values).

Finally, like most other work on campaign strategy, the implications of our findings for democratic respon siveness remain unclear (although see Sulkin 2005). Do officeholders who emphasize issues in their campaigns pursue these issues once elected? Does highlighting certain personal features lead elected officials to be haviors aimed at sustaining those features? Do candi dates who place weight on their parties subsequently behave as loyal partisans? If not, is it disingenuous of representatives to emphasize these factors? If so, what does it mean for representation that aspects of respon siveness are driven, in part, by the candidate's status as an incumbent or challenger?42 These are critical ques tions about democratic representation and require an explicit link be made between work on campaigns and studies of governing behavior.

APPENDIX A: SURVEY OF WEB PRODUCERS

We conducted a survey of individuals involved in the creation of congressional campaign Web sites. We identified potential respondents by accessing the universe of U.S. Senate and House campaign Web sites in 2008. We contacted the 716 campaigns that provided a workable e-mail address or on line inquiry form on October 17. We followed up, on subse quent days, by calling each campaign (when a phone number was provided). We asked that an individual involved in the creation and/or updating of the campaign's Web site either complete a confidential 5-minute on-line survey or e-mail the embedded survey back to us. We contacted each campaign up to three times (with the last contact occurring on November 5), receiving a total of 137 responses (a 19.13% response rate, which falls within a typical range; see Couper 2008, 340).43 The sample reflected the population of campaigns fairly well in terms of office (14% came from Senate campaigns), party

the dynamic stems from a reaction to the opponent or from a mutual desire (by both campaigns) to cater to the tastes of the voters in the district/state (even if suitable instrumental variables could be discovered, it would remain unclear). In future work, one way to explore this would be to add an explicit time component to the analyses. 42 One fruitful route may be to compare representatives' Web sites (e.g., Esterling, Lazer, and Neblo 2005) with their campaign Web sites.

43 We thank Jennifer Stromer-Galley for advice (see Foot and Schneider 2006, 225; Stromer-Galley et al. 2003).

358

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

(53% carne from Democratic campaigns), and status (31% came from incumbents, 53% came from challengers, and 15% came from open seats). We asked respondents, on a seven point scale, to indicate the extent to which they are informed about how the content of the site is determined, with higher scores indicating more knowledge. The average response is 6.51 (std. dev. = 1.16; N = 136).

In addition to the items described in the text, we asked re

spondents to rate how well various forms of communication "capture the campaign's overall strategy (e.g., the message your campaign hopes to relay to voters at large, as opposed to more targeted messages)" on a seven-point scale, with higher scores indicating fuller capture of the overall strategy. Respondents rated the Web site (mean = 5.88; std. dev. = 1.50; N = 109) as significantly more representative than all other media, followed by speeches (5.63; 1.54; 111), in formal conversations (5.57; 1.66; 109), television advertise

ments (for those campaigns that had ads; 4.99; 2.19; 69), direct mail (4.86; 1.91; 98), and media coverage (4.72; 1.81; 107) (e.g., comparing the Web to speeches gives tm = 1.63, p < .11 for a two-tailed test). The lower score for television advertisements may reflect the aforementioned information constraint as well as targeting towards particular audiences (e.g., Goldstein 2004). Relatedly, respondents reported that 91% of other campaign material included the campaign Web site's address.

Another item on the survey asked respondents to rate the importance of various goals for their Web sites on a seven point scale, with higher scores indicating increased impor tance. Of note is that the top-rated activities are those aimed at information provision (e.g., about issues and personal background) and persuasion. Respondents rated fundraising and volunteer-oriented activities as dramatically (and signif icantly) less important (see Foot and Schneider 2006, 170 and Stromer-Galley et al. 2003 for similar results from their 2002-3 survey).

APPENDIX B: COMPARISONS WITH TELEVISION ADVERTISING AND NEWSPAPER COVERAGE

To compare the tone of rhetoric on our Web sites with television advertising and newspaper coverage, we used data from the Wisconsin Advertising Project for 2002 and 2004 (for candidates who produced advertisements, meaning a total of 232 candidates, or 52% of the candidates in our sample) and data from our own content analysis of newspaper coverage of Senate campaigns from 2002 through 2006. (Note that this newspaper content analysis is distinct?although it overlaps?from the data presented in Table 1.) In analyzing the newspapers, we coded each distinct statement attributed to the campaign in up to 30 randomly drawn articles from the state's major newspaper, for all states that had an available electronic newspaper (a total of 157 candidates, which equals 79% of our Senate sample); (see Lau and Pomper 2004).44 For the television advertising comparison, we find a highly significant relationship such that those who did not

44 We exclude House races because major newspapers pay little to no attention to most House races. We coded articles for all Senate

races (in our Web sample) for which an electronic version of a major newspaper from the state was available. Following Lau and Pomper (2004), we coded each distinct statement attributed to a campaign

within each article. There could be multiple statements within each article. If we identified more than 30 articles, we drew a random sam

ple of 30. The average number of articles coded for each candidate is 26.42 (std. dev. = 6.92; N = 157). The average number of statements

go negative on their Web sites produce, on the average, only 1.02 (se = 0.17; N = 124) negative television advertisements, compared to 1.87 (0.20; 105) negative advertisements for those who went negative on their Web sites (t22i = 3.22, p < .Ol).45 Similarly, for newspaper coverage, those who did not go negative on the Web had, on the average, only 1.29 (0.38; N = 59) negative statements attributed to them, whereas those who went negative had 4.32 (0.72; 92) attributed negative statements (tU9 = 3.18, p < .Ol).46

APPENDIX C: INDEPENDENT VARIABLES

In Table C.l, we display the additional variables included in our analyses (see Appendix D), along with some descriptive statistics. All of these data are measured at the candidate level, and, unless otherwise noted, the data come from The

Almanac of American Politics (complemented by the Na tional Journal Web site). For all analyses, we included vari ables that prior work shows have significant effects on cam paign behavior. We included additional independent vari ables for certain dependent variables (either because prior work on that variable suggests it, or because it strikes us as an obviously relevant factor). The last column of Table C.l lists the dependent variable(s) for which the given variable is included.

Variables included in all analyses that are dichotomous indicators include year (2004, 2006), office (Senate), party (Democrat), and gender (Female). We also include front-runner status in all analyses, because it is a prominent variable in some prior work (e.g., Buell and Sigelman 2008; Skaperdas and Grofman 1995), and it correlates with candidate status (e.g., incumbents are typically front-runners, and it also, as noted in the text, impacts the behavior of open seat candidates). We measure front-runner status by taking the difference between a candidate's support (measured in the proportion of the vote he or she received in the election) and the support for his or her opponent, and then creating three categories of "clear front-runner," "not clear trailer or front-runner," and "clear trailer" (e.g., Lau and Pomper 2004: 35).47

We measure a campaign's resources by the amount of money each candidate raised (in millions of dollars) as

is 30.43 (18.68; 157). Further coding details (and reliability analyses) are available from the authors.

45 Television advertisements differ from Web sites insofar as candi

dates who produce advertisements typically develop more than one (but all candidates have a single Web site). This is why we compare the number of negative television advertisements produced, on the average, for candidates who went negative on their sites compared to those who did not go negative on their sites. Our statistics include only candidates who produced television advertisements. Of these candidates, the average number of advertisements produced is 6.90 (6.0; 232). The average number of advertisements produced by all candidates is 3.61 (5.54; 444). Also, our statistics include television attack advertisements only. If we merged attack and contrast adver tisements, the respective means are 3.64 (0.41; 124) and 4.58 (0.44; 105) (r227 = 1.57,/? < .06) (see Franz et al. 2008,121). If we include all candidates, regardless of whether they produced an ad, the respective attack advertisement means are 0.5 (0.09; 254) and 1.05 (0.13; 186) (i438 = 3.61,/? < .01), while the attack and contrast advertisements

means are 1.78 (0.23; 254) advertisements compared to 2.59 (0.30; 186) (?438 = 2.19,/? < .01). 46 The results are virtually the same if we limit the analysis to races with 16 or more articles (e.g., Lau and Pomper 2004). 47 Our front-runners won by more than 10%, whereas our trailers lost by at least 10%. Others were in the middle category.

359

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

TABLE C.1. Independent Variables

Variable Measure Percentage/Mean

(std. dev.) Dependent Variable

Candidate status (Challenger, open seat)

Competition

Year (2004, 2006)

Office (Senate)

Party (Democrat)

Gender (Female)

Funds raised

Front-runner status

District/state Republican partisanship (district Republican)

Opponent negativity

Issue salience

District/state Republican partisanship x Democrat

2004 x Democrat

2006 x Democrat

Held prior office

Two dichotomous variables indicating challenger status or open seat status (baseline is incumbent).

Four point Cook rating with 0 = solid Democratic or Republican; .33 = likely Democratic or Republican; .67 = leaning Democratic or Republican; 1 = toss-up.

Two dichotomous variables indicating 2004 and 2006 (baseline is 2002).

Dichotomous variable indicating Senate candidate (baseline is House candidate).

Dichotomous variable indicating Democratic party candidate (baseline is Republican party candidate).

Dichotomous variable indicating female (baseline is male).

Amount of money candidate raised (according to the Federal Election Commissions).

Three point rating with 0 = clear trailer; .5 = not clear trailer or front-runner; 1 = clear front-runner.

Percentage of district/state voters for Bush in 2000/2004.

Dichotomous variable indicating opponent's negative statement about the candidate.

Weighted national importance of issues discussed (based on public opinion "most important issues" measures). (The range is 0% to 50.50%.)

Interaction between district/state

partisanship and Democratic party candidate.

Interaction between year 2004 and Democratic party candidate.

Interaction between year 2006 and Democratic party candidate.

Dichotomous variable indicating holding of prior elected office.

41.85% challengers 13.59% open seat

67.66% solid 8.02% likely 11.28% leaning 13.04% toss-up

36.55% 2004 39.67% 2006 25.95% Senate

48.10% Democrats

17.12% Females

$2,257,233 ($3,598,908) (On 0-1 standardized

scale) 39.67% clear trailer 19.29% not clear trailer or

front-runner 41.03% clear front-runner 51.21% (11.25%) for

Bush

44.70%

13.21% (7.38%)

24.50% (26.65%) for Bush

17.53%

20.11%

67.93%

All

All

All

All

All

All

All

All

All

Negativity, issue negativity, personal negativity

Issue ownership

Issue ownership, party emphasis

Issue ownership, party emphasis

Issue ownership, party emphasis

Prior office

experience, familiarity, district benefits

reported by the Federal Election Commission (FEC). The FEC failed to report financial data for 18 of our 736 candi dates. Given the importance of funds in general, we opt to report analyses with the fund-raising variable included and, thus, we exclude the 18 missing cases (resulting in an N of 718). Our results are unchanged if we exclude fundraising and run the analyses on all 736 cases. We measure "District/State (D/S) Republican Vote," for

2002 and 2004, with the percentage of votes in the dis trict/state cast for George W. Bush in 2000, and for 2006

with the percentage of votes cast for Bush in 2004 (Carson, Engstrom and Roberts 2006; Lau and Pomper 2004). We also collected data on other district/state features such as per

centage urban, percentage with high school diploma, median income, and percentage of homes in the state with Internet connections; we do not include these variables in the analyses, as their inclusion does not change the results.

For our negativity regressions, we include a variable that indicates whether the candidate's opponent went neg ative on his or her Web site, because other work suggests that a negative statement triggers a negative response (see

Ansolabehere and Iyengar 1995; Kahn and Kenney 1999; Lau and Pomper 2004, 33). For our issue ownership model, we add a variable to control for the salience of the is sues discussed in order to test for the possibility that issue ownership stems from a party's issues being publicly salient

360

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

TABLE D.1. Going Negative and Interactivity (Figure 2)

Negativity Issue negativity Personal negativity Interactivity

Challenger

Open seat

Competition

2004

2006

Senate

Democrat

Female

Funds raised

Front-runner status

District Republican

Opponent negativity

Constant

Log likelihoodN

1.45***

(0.36) 0.28 (0.33) 1.75***

(0.32) 0.61*** (0.26) 1.07***

(0.26) 0.33 (0.28) 0.50*** (0.20) 0.41* (0.26) 2.16* (1.48)

? 1 74***

(0?37) -0.001

(0.01) 0.21 (0.24)

-1.57*** (0.60)

-337.61 714

1.76**

(0.39) 0.50* (0.38) 0.95** (0.34)

-0.37** (0.22)

0.27 (0.32) 0.26 (0.22) 0.45* (0.28) 2.61** (1.53)

-1.63*** (0.40)

-0.002 (0.01) 0.55** (0.29)

-0.99* (0.66)

-268.23 546

0.82** (0.39) 0.66** (0.40) 1.66***

(0.34) -0.92***

(0.23)

0.07 (0.31) 0.61*** (0.24)

-0.01 (0.29) 1.10 (1.39)

-1.79*** (0.43)

-0.01 (0.01) 0.44* (0.28)

-0.76 (0.68)

-256.94 546

0.43* (0.32) 0.37 (0.31) 0.22 (0.26) 0.67*** (0.25) 0.78*** (0.25) 0.30 (0.25) 0.67*** (0.18)

-0.10 (0.23) 2.63** (1.30)

-0.05 (0.33) 0.01 (0.01)

-2.71*** (0.57)

-406.22 718

Note: Entries are logit coefficients with standard errors in parentheses, one-tailed tests.

*p < .01; **p < .05; *p < .10 for

(see Sides 2006). We constructed our issue saliency measure based on data from Harris Interactive's "two most im

portant issues" question.48 Also, for our issue ownership analysis, as well as the party emphasis regression, we add three other variables. This includes an interaction be tween Democratic candidate status and district ideology, due to the possibility of a negative impact of district ide ology (measured in the Republican direction), particularly for Democratic candidates (see Abramowitz, Alexander, and Gunning 2006). We also include interactions for year (2004 and 2006) and Democratic candidate status because, over the time of our data, the Democratic Party's rela tive approval continually grew, and thus, Democratic candi dates had increasing incentives to emphasize partisan-related features.49

48 Candidates receive points based on the degree of issue saliency for each issue they discuss in each year. For example, a candidate in 2002 would receive 9.67 points for every time he or she mentioned Education because 9.67% of the public thought Education to be one of the two most important issues for the government to deal with in that year. We then summed the saliency score for all issues the candidate mentioned each year and divided by the number of issues mentioned.

49 The Republican Party's favorability ratings (according to Gallup) dropped in the respective years from 54.7% to 51.7% to 38.6%. The Democratic favorability ratings stayed relatively stable at around 53% meaning that their relative advantage grew over time. This also parallels President Bush's declining approval.

Finally, for our three incumbent dependent variables prior office experience, familiarity, and district benefits?we add a variable indicating whether the candidate held any prior office. This is an important control to preclude the possibility that an incumbency effect does not only reflect the fact that the incumbent held a prior office and thus can emphasize those experiences.

APPENDIX D: ANALYSES

In Tables D.1-D.4, we report regressions akin to the ones used to generate the probabilities presented in Figure 2. The exceptions involve the interval level dependent variables. In this Appendix, we use the full range of these variables, but in Figure 2, we report probabilities based on regressions that transformed the variables to dichotomous measures indicat

ing whether the candidate was below or above the mean value. Also, in this Appendix, the incumbency regressions that include interactions between candidate status and com petition use the full four-point competition scale; however, as noted in the text, Figure 3 is based on a three-point competition scale that collapses likely and leaning races. All analyses for the figures are available from the authors. Also, for all analyses, we recoded the independent variables to be on 0 to 1 scales. We also use one-tailed tests, because our predictions have clear directional content (Blalock 1979, 163).

361

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

TABLE D.2. Issues and Party Emphasis (Figure 2)

Issue ownership Positions Endorsements Party emphasis

Challenger

Open seat

Competition

2004

2006

Senate

Democrat

Female

Funds raised

Front-runner status

District Republican

Issue salience

District Republican x Democrat

2004 x Democrat

2006 x Democrat

Constant

f?2/log likelihoodN

1.25* (0.80) 1.11* (0.76) 0.54 (0.64)

-5.73*** (0.75)

-11.90*** (0.75) 0.25 (0.60) 4.47** (2.50) 0.45 (0.56)

-6.25** (3.18) 1.35* (0.89) 0.02 (0.03) 0.07** (0.03)

-0.06 (0.05) 8.92*** (1.12)

20.49*** (1.13)

-1.08 (1.80)

0.68 701

0.22** (0.11) 0.21** (0.10) 0.03 (0.09) 0.09 (0.08) 0.13** (0.08)

-0.03 (0.08) 0.03 (0.06) 0.08 (0.07) 0.06 (0.42) 0.03 (0.11) 0.001 (0.003)

0.71*** (0.26) 0.53*** (0.23) 0.51*** (0.21) 0.22 (0.18) 0.29** (0.17) 0.18 (0.21) 0.42*** (0.13) 0.18 (0.17) 0.89 (1.36) 0.59** (0.27)

-0.01 (0.01)

0.24* (0.18) 0.00 (0.00)

-1068.34 718

-j 47***

(0.46) 2.77 (0.16)

-2265.04 718

1.52**

(0.68) 0.07 (0.65)

-0.60 (0.50)

-0.14 (0.61)

-1.07* (0.75)

-0.21 (0.44) 5.12** (1.88) 0.36 (0.34)

-1.04 (2.32) 0.31 (0.72) 0.04* (0.03)

-0.10*** (0.04) 0.36 (0.83) 2.10** (0.92)

-5.62*** (1.60)

-180.86 718

Note: Entries are coefficients with standard errors in brackets. Issue ownership is a least squared regression. Positions and endorsements are negative binomial regressions. Party emphasis is a logit regression. ***p < .01 ; **p < .05; *p < .10 for one-tailed tests.

362

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

TABLE D.3. Personal Features (Figure 2)

Leadership Competence Empathy Polls

Challenger

Open seat

Competition

2004

2006

Senate

Democrat

Female

Funds raised

Front-runner status

District Republican

Constant

Log likelihoodN

0.77*** (0.31) 0.43* (0.30) 0.35* (0.25) 0.29* (0.23) 0.45** (0.22) 0.08 (0.24) 0.55*** (0.17)

-0.23 (0.22)

-0.63 (1.29)

-0.45* (0.32) 0.01 (0.01)

-1.66*** (0.52)

-431.37 718

1.56***

(0.50) 1.03***

(0.40) 0.71** (0.39)

-0.07 (0.28) 0.11 (0.29) 0.02 (0.33) 0.35* (0.23)

-0.25 (0.29)

-1.85 (1.57)

-0.74* (0.49) 0.03*** (0.01) 0.02 (0.73)

-284.09 718

0.50** (0.30)

-0.05 (0.28) 0.44** (0.24)

-0.48** (0.21)

-0.17 (0.20) 0.01 (0.23) 0.17 (0.16) 0.28* (0.21) 1.98* (1.27)

-0.25 (0.30) 0.01 (0.01)

-0.65* (0.50)

-473.03 715

1.75**

(0.43) 0.85** (0.45) 1.98**

(0.35) -0.73** (0.28)

-0.24 (0.41) 0.13 (0.27)

-0.31 (0.36) 1.47

(1.65) 0.83** (0.47)

-0.01 (0.01)

-3.09*** (0.79)

-197.61 548

Note: Entries are logit coefficients with standard errors in brackets. ***p < .01; **p < .05; *p < .10 for one-tailed tests.

363

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

TABLE D.4. Incumbency (Figures 2 and 3)

Prior office

experience Familiarity

District benefits

Prior office

experience Familiarity

District benefits

Challenger

Open seat

Competition

2004

2006

Senate

Democrat

Female

Funds Raised

Front-Runner Status

District Republican

Held Prior Office

Competition x Challenger

Competition x Open seat

Constant

Log likelihoodN

-0.83** (0.44)

-0.56* (0.43) 0.58** (0.35)

-0.12 (0.30)

-0.26 (0.30) 0.38 (0.32)

-0.32* (0.23) 0.36 (0.30)

-1.51 (1.53) 0.29 (0.43)

-0.01 (0.01) 2.80** (0.29)

0.06 (0.72)

-278.01 715

-0.59** (0.32)

-0.14 (0.30) 0.30 (0.26)

-0.24 (0.21)

-0.04 (0.21) 0.36* (0.24)

-0.25* (0.16) 0.04 (0.21)

-1.93* (1.22)

-0.08 (0.32) 0.02** (0.01) 0.11 (0.23)

0.18 (0.53)

-461.68 718

-0.56*** (0.17)

-0.39*** (0.15) 0.17* (0.13)

-0.01 (0.12) 0.26*** (0.11) Q 44***

(o!l2) 0.11 (0.09) 0.03 (0.11)

-0.54 (0.58) 0 44***

(o!l7) 0.003 (0.004) 0.21* (0.15)

-0.82*** (0.31) 0.05 (0.08)

-849.63 718

-0.12 (0.58)

-0.32 (0.56) 1.82**

(0.91) -0.13

(0.30) -0.27

(0.30) 0.35 (0.32)

-0.30* (0.23) 0.32 (0.30)

-1.57 (1.53) 0.77* (0.49)

-0.01 (0.01) 2.87*** (0.29)

-1.94** (1.08)

-0.90 (1.11)

-0.56 (0.79)

-276.00 715

-0.12 (0.44)

-0.04 (0.42) 0.78* (0.46)

-0.24 (0.21)

-0.04 (0.21) 0.34* (0.24)

-0.24* (0.16) 0.01 (0.22)

-1.94* (1.23) 0.24 (0.38) 0.02** (0.01) 0.17 (0.24)

-0.98* (0.64)

-0.22 (0.68)

-0.23 (0.59)

-460.34 718

-0.32* (0.25)

-0.20 (0.22) 0.37** (0.18)

-0.01 (0.12) 0.25*** (0.11) 0.45*** (0.12) 0.12* (0.09) 0.02 (0.11)

-0.55 (0.58) 0.61*** (0.21) 0.004 (0.004) 0.25** (0.16)

-0.47* (0.34)

-0.35 (0.33)

-1.05*** (0.35) 0.04 (0.08)

-848.45 718

Note: Entries are coefficients with standard errors in brackets. Prior office experience and familiarity are logits. District benefits is a negative binomial regression. ***p < .01; **p < .05; *p < .10 for one-tailed tests.

364

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

American Political Science Review Vol. 103, No. 3

REFERENCES

Abramowitz, Alan I., Brad Alexander, and Matthew Gunning. 2006. "Incumbency, Redistricting, and the Decline of Competition in U.S. House Elections." Journal of Politics 68: 75-88.

Ansolabehere, Stephen, and Shanto Iyengar. 1995. Going Negative: How Political Advertisements Shrink and Polarize the Electorate. New York: The Free Press.

Ansolabehere, Stephen, and James M. Snyder. 2002. "The Incum bency Advantage in U.S. Elections: An Analysis of State and Federal Offices, 1942-2000." Election Law Journal 1: 315-38.

Ansolabehere, Stephen, and James M. Snyder. 2004. "Using Term Limits to Estimate Incumbency Advantages When Officeholders Retire Strategically." Legislative Studies Quarterly 29: 487-515.

Baumeister, Roy. F, Ellen Bratslavsky, Catrin Fickenauer, and Kathleen D. Vohs. 2001. "Bad Is Stronger Than Good." Review of General Psychology 5: 323-70.

Berelson, Bernhard R., Paul F. Lazarsfeld, and William N. McPhee. 1954. Voting: A Study of Opinion Formation in a Presidential Cam paign. Chicago: University of Chicago Press.

Bimber, Bruce, and Richard Davis. 2003. Campaigning Online: The Internet in U.S. Elections. New York: Oxford University Press.

Blalock, Hubert M., Jr. 1979. Social Statistics. 2nd ed. New York: McGraw-Hill.

Buey, Erik P. 2004. "Interactivity in Society: Locating an Elusive Concept." The Information Society 20: 373-83.

Buell, Emmett H., Jr., and Lee Sigelman. 2008. Attack Politics. Lawrence, KS: University Press of Kansas.

Carson, Jamie L., Erik J. Engstrom, and Jason M. Roberts. 2006. "Re districting, Candidate Entry, and U.S. House Elections." American Political Science Review 50: 283-93.

Chadwick, Andrew. 2006. Internet Politics: States, Citizens, and New Communication Technologies. New York: Oxford University Press.

Chinni, Dante. 2002. Oct. 29. How the Web Is Changing Elec tion Campaigns. Christian Science Monitor (on-line edition). <http://www.csmonitor.com/2002/1029/p02s01-uspo.html>. (Au gust 2, 2007).

Couper, Mick P. 2008. Designing Effective Web Surveys. New York: Cambridge University Press.

Democracy Online Project. 1999. Online Campaigning: A Primer. Washington, DC: Graduate School of Political Management, George Washington University.

Dolan, Kathleen. 2005. "Do Women Candidates Play to Gender Stereotypes? Do Men Candidates Play to Women? Candidate Sex and Issues Priorities on Campaign Web Sites." Political Research Quarterly 58: 31-44.

Downs, Anthony. 1957. An Economic Theory of Democracy. New York: Harper Collins.

Druckman, James N. 2004. "Political Preference Formation: Com petition, Deliberation, and the (Ir)relevance of Framing Effects." American Political Science Review 98: 671-86.

Druckman, James N, Lawrence R. Jacobs, and Eric Ostermeier. 2004.

"Candidate Strategies to Prime Issues and Image." The Journal of Politics 66:1205-27.

Druckman, James N, Martin J. Kifer, and Michael Parkin. 2007. "The

Technological Development of Candidate Web Sites: How and Why Candidates Use Web Innovations." Social Science Computer Review 25: 425-42.

Druckman, James N, Martin J. Kifer, and Michael Parkin. N.d. "Timeless Strategy Meets New Medium: Going Negative on Con gressional Campaign Web Sites, 2002-2006." Political Communi cation. Forthcoming.

Druckman, James N, and Rose McDermott. 2008. "Emotion and the Framing of Risky Choice "Political Behavior 30: 297-321.

Esterling, Kevin M., David M. J. Lazer, and Michael A. Neblo. 2005. "Home (Page) Style: Determinants of the Quality of House Mem bers' Web Sites." International Journal of Electronic Government Research 1: 50-63.

Eveland, William P., and Sharon Dunwoody. 2002. "An Investigation of Elaboration and Selective Scanning as Mediators of Learning from the Web and Print." Journal of Broadcasting and Electronic

Media 46: 34-53. Fenno, Richard. 1978. Homestyle: House Members in Their Districts.

Glenview, IL: Scott Foresman, and Company.

Fiorina, Morris P. 1989. Congress: Keystone of the Washington Estab lishment. 2nd ed. New Haven, CT: Yale University Press.

Fiorina, Morris P. 2004. "Keystone Reconsidered." In Congress Re considered, ed. Lawrence C. Dodd and Bruce I. Oppenheimer.

Washington, DC: Congressional Quarterly Press. Foot, Kirsten A., and Steven M. Schneider. 2006. Web Campaigning.

Cambridge: MIT Press. Franklin, Charles H. 1991. "Eschewing Obfuscation? Campaigns and

the Perception of U.S. Senate Incumbents." American Political Science Review 85:1193-1214.

Franz, Michael M., Paul B. Freedman, Kenneth M. Goldstein, and Travis N. Ridout. 2008. Campaign Advertising and American Democracy. Philadelphia: Temple University Press.

Funk, Carolyn L. 1999. "Bringing the Candidate into Models of Candidate Evaluations." Journal of Politics 61: 700-720.

Geer, John G. 2006. In Defense of Negativity: Attack Ads in Presi dential Campaigns. Chicago: University of Chicago Press.

Gerber, Alan S. 2004. "Does Campaign Spending Work? Field Ex periments Provide Evidence and Suggest New Theory." American Behavioral Scientist 47: 541-74.

Goldstein, Kenneth M. 2004. "What Did They See and When Did They See It?" In The Medium and the Message, ed. Kenneth M. Goldstein and Patricia Strach. Upper Saddle River, NJ: Pearson, Prentice-Hall, 27-42.

Goldstein, Kenneth M., and Paul Freedman. 2002. "Campaign Ad vertising and Voter Turnout: New Evidence for a Stimulation Ef fect." Journal of Politics 64: 721-40.

Goldstein, Kenneth M., and Joel Rivlin. 2005. Political Advertising in the 2002 Elections, <http://www.polisci.wisc.edu/tvadvertising/ Political%20Advertising%20in%20the%202002%20Elections. htm>. (April 17,2006).

Gronke, Paul. 2000. The Electorate, the Campaign, and the Office: A Unified Approach to Senate and House Elections. Ann Arbor: University of Michigan Press.

Groseclose, Timothy. 2001. "A Model of Candidate Location When One Candidate Has a Valence Advantage." American Journal of Political Science 45: 862-86.

Hayes, Danny. 2005. "Candidate Quality through a Partisan Lens: A Theory of Trait Ownership." American Journal of Political Science 49: 908-23.

Ireland, Emilienne, and Phil Tajitsu Nash. 2001. Winning Campaigns Online: Strategies for Candidates and Causes, 2nd ed. Bethesda, MD: Science Writers Press.

lyengar, Shanto, and Donald R. Kinder. 1987. News That Matters. Chicago: University of Chicago Press.

Jacobs, Lawrence R., and Robert Y. Shapiro. 1994. "Issues, Candi date Image, and Priming: The Use of Private Polls in Kennedy's 1960 Presidential Campaign." American Political Science Review 88: 527-40.

Jacobson, Gary. 1992. The Politics of Congressional Elections, 3rd ed. New York: Harper Collins.

Jacobson, Gary. 2004. The Politics of Congressional Elections, 6th ed. New York: Pearson Longman.

Kahn, Kim Fridkin, and Patrick J. Kenney. 1999. The Spectacle of U.S. Senate Campaigns. Princeton, NS: Princeton University Press.

Kahn, Kim Fridkin, and Patrick J. Kenney. 2004. No Holds Barred: Negativity in U.S. Senate Campaigns. Upper Saddle River, NJ: Pearson, Prentice-Hall.

Kern, Montague. 1989.30-Second Politics: Political Advertising in the 80's. New York: Praeger.

Kinder, Donald R. 1986. "Presidential Character Revisited." In Po litical Cognition: The 19th Annual Carnegie Symposium on Cog nition, ed. Richard R. Lau and David O. Sears. Hillsdale, NJ: Erlbaum, 233-55.

Kinder, Donald R. 1998. "Opinion and Actions in the Realm of Poli tics" In The Handbook of Social Psychology, ed. Daniel T. Gilbert, Susan T. Fiske and Gardner Lindzey. Boston, MA: McGraw-Hill, 778-867.

Koch, Jeffrey. 2008. "Has the Importance of the Incumbency Advan tage Diminished in House Elections?" Presented at the annual

meeting of the American Political Science Association, Philadel phia, August 31-September 2.

Latimer, Christopher P. 2007. "Utilizing the Internet as a Campaign Tool: The Relationship between Incumbency, Political Party Affil iation, Election Outcomes, and the Quality of Campaign Websites

365

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms

Campaign Communications in U.S. Congressional Elections August 2009

in the United States." Journal of Information Technology and Pol itics 4: 81-95.

Lau, Richard R., and Gerald M. Pomper. 2004. Negative Campaign ing: An Analysis of U.S. Senate Elections. New York: Rowman and Littlefield.

Lau, Richard R., and David P. Redlawsk. 2006. How Voters Decide: Information Processing in Election Campaigns. Cambridge, MA: Cambridge University Press.

Lin, Yan. 2004. "Fragmentation of the Structure of Political Commu nication Research: Diversification or Isolation?" In Handbook of Political Communication Research, ed. Lynda Lee Kaid. Mahwah, NJ: Lawrence Erlbaum Associates, 69-108.

Lipinski, Daniel. 2004. Congressional Communication: Content and Consequences. Ann Arbor, MI: University of Michigan Press.

Lupia, Arthur, and Mathew D. McCubbins. 1998. The Democratic Dilemma. New York: Cambridge University Press.

Marcus, George E., W. Russell Neuman, and Michael MacKuen. 2000. Affective Intelligence and Political Judgment. Chicago: Uni versity of Chicago Press.

Mark, David. 2006. Going Dirty: The Art of Negative Campaigning. Lanham, MD: Rowman and Littlefield.

McDermott, Rose, James H. Fowler, and Oleg Smirnov. 2008. "On the Evolutionary Origin of Prospect Theory Preferences." Journal of Politics 70: 335-50.

Miller, Joanne M., and Jon A. Krosnick. 1996. "News Media Impact on the Ingredients of Presidential Evaluations." In Political Persua sion and Attitude Change, ed. Diana C. Mutz, Paul M. Sniderman, and Richard A. Brody. Ann Arbor, MI: University of Michigan Press, 79-100.

Neuendorf, Kimberly A. 2002. The Content Analysis Guidebook. Thousand Oaks, CA: Sage Publications.

Newman, Bruce 1.1999. Ed. Handbook of Political Marketing. Thou sand Oaks, CA: Sage Publications.

Newman, Bruce I., and Richard M. Perloff. 2004. "Political Mar keting." In Handbook of Political Communication Research, ed. Lynda Lee Kaid. Mahwah, NJ: Lawrence Erlbaum Associates, 17 44.

Niemi, Richard G, and Herbert F. Weisberg. 1993. Classics in Voting Behavior. Washington, DC: CQ Press.

Page, Benjamin 1.1978. Choices and Echoes in Presidential Elections: Rational Man and Electoral Democracy. Chicago: University of Chicago Press.

Palmer, Jerry. 2004. "Source Strategies and Media Audiences." Jour nal of Political Marketing 4: 57-77.

Perloff, Richard M. 2002. "Political Campaign Persuasion and Its Discontents." In The Persuasion Handbook, ed. James Price Dillard, and Michael Pfau. Thousand Oaks, CA: Sage Publications.

Petrocik, John R. 1996. "Issue Ownership in Presidential Elections, with a 1980 Case Study." American Journal of Political Science 40: 825-50.

Rahn, Wendy M., John H. Aldrich, Eugene Borgida, and John L. Sullivan. 1990. "A Social-Cognitive Model of Candidate Ap proval." In Information and Democratic Processes, ed. John Ferejohn and James Kuklinki. Urbana: University of Illinois Press.

Riffe, Daniel, Stephen Lacy, and Frederick G. Fico. 1998. Analyzing Media Messages. Mahwah, NJ: Lawrence Erlbaum Associates.

Riker, William H. 1996. The Strategy of Rhetoric, ed. Randell L. Calvert, John Mueller, and Rick Wilson. New Haven, CT: Yale University Press.

Schattschneider, E. E. 1960. The Semi-sovereign People: A Realist's View of Democracy in America. New York: Holt, Rinehart, and Winston.

Sellers, Patrick. 1998. "Strategy and Background in Congressional Campaigns." American Political Science Review 92:159-71.

Semiatin, Richard. 2005. Campaigns in the 21st Century. New York: McGraw-Hill.

Shaw, Daron R. 1999. "The Effect of TV Ads and Candidate Ap pearances on Statewide Presidential Votes, 1988-96." American Political Science Review 83: 345-61.

Sides, John M. 2006. "The Origins of Campaign Agendas." British Journal of Political Science 36: 407-36.

Sigelman, Lee, and Emmett H. Buell, Jr. 2003. "You Take the High Road and I'll Take the Low Road? The Interplay of Attack Strate gies and Tactics in Presidential Campaigns." Journal of Politics 65: 518-31.

Simon, Adam F. 2002. The Winning Message: Candidate Behavior, Campaign Discourse, and Democracy. Cambridge, MA: Cam bridge University Press.

Skaperdas, Stergios, and Bernard Grofman. 1995. "Modeling Neg ative Campaigning." American Political Science Review 89: 49 61.

Southwell, Brian G, and Mira Lee. 2004. "A Pitfall of New Media? User Controls Exacerbate Editing Effects on Memory." Journal ism and Mass Communication Quarterly 81: 643-56.

Sniderman, Paul M., Richard A. Brody, and Philip E. Tetlock. 1991. Reasoning and Choice: Explorations in Political Psychology. New York: Cambridge University Press.

Stromer-Galley, Jennifer, Philip N. Howard, Steven M. Schneider, and Kirsten A. Foot. 2003. "The New Political Campaign Position: A Survey of Web Site Producers and Managers." Presented at annual meeting of the International Communication Association, San Diego (May).

Sulkin, Tracy. 2001. "Explaining Campaign Intensity." America Pol itics Research 29: 608-24.

Sulkin, Tracy. 2005. Issue Politics in Congress. New York: Cambridge University Press.

Sulkin, Tracy, and Jillian Evans. 2006. "Dynamics of Diffusion: Ag gregate Patterns in Congressional Campaign Agendas." American Politics Research 34: 505-34.

Tomz, Michael, Jason Wittenberg, and Gary King. 1999. "Clar ify." Version 1.2.1. Cambridge, MA: Harvard University, June 1. <http://gking.harvard.edu/> (Accessed January 2009).

Trent, Judith S., and Robert V. Friedenberg. 2008. Political Campaign Communication. New York: Rowman and Littlefield.

Wason, Peter C. 1959. "The Processing of Positive and Negative Information." The Quarterly Journal of Experimental Psychology 11: 92-107.

Zaller, John. 1992. The Nature and Origins of Public Opinion. New York: Cambridge University Press.

366

This content downloaded from ������������132.174.253.170 on Mon, 14 Nov 2022 13:34:41 UTC������������

All use subject to https://about.jstor.org/terms