Sampling Strategy and Codebook for Content Analysis
be coded more than once, multiple people will code the same article; an average of different codes of the same article will be the number that’s recorded.
Codebook Measures: One article
Codes: 1. Positivity 2. Valence of headline 3. Presence of counterargument 4. Headline’s representativeness of the article 5. Application of statistics
1. Positivity Conceptual Definition- Positivity is when someone shows support for an issue
or cause. Operational Definition- Positivity in an article can be measured by looking at the amount of favorability or support it shows towards an issue or cause.
x=0 (Absence of Positivity) An article without positivity for Bernie Sanders’ college tuition plan will display unfavorable rhetoric. For example, an article with no positivity for Sanders’ free college proposal might quote people who don’t want to pay higher taxes for students that they might perceive as lazy. In other words, negative rhetoric towards Sanders’ proposal would qualify the article as being absent of positivity. y=1 (Presence of Positivity) An article with positivity towards Bernie Sanders’ college tuition plan will talk about his plan in a favorable light. For example, an article that has positivity for Sanders’ proposal of free college might cite direct experiences from college students who are in massive debt, and advocate for the alleviation of their financial situations. 2. Valence of headline (Entman, 2010) Conceptual Definition- The valence of a headline is the degree to which it’s vocabulary
frames a story (Entman, 2010). Operational Definition- The valence of a headline can be measured by the language used in
the title, which can hold positive or negative connotations. x=0 (Negative Valence) A headline with a negative valence in an article about Bernie Sanders’ plan for free college will use unfavorable language. For example, a headline with a negative valence may represent Sanders’ plan with the words “impractical” or “far-fetched,” thus promoting a negative spin or bias.
y=1 (Positive Valence) A headline with a positive valence in an article about Bernie Sanders’ plan involving free
college will use supportive language. For example, a headline with a positive valence may state that Sanders’ plan is beneficial or advantageous to all students, promoting a positive spin or bias.
3. Presence of counterargument Conceptual Definition- A counterargument is when another point of view is presented to
the majority opinion on a certain issue or topic. Operational Definition- The presence of a counterargument in an article can be measured by seeing if more than one point of view are applied to an issue. x=0 (Absence of Counterargument) A counterargument is absent in an article when only one point of view is presented. For example, if an article about Bernie Sanders only contains a point of view that is against his proposal of free college, no counterargument is present. y=1 (Presence of Counterargument) A counterargument is present in an article when both points of view on an issue are presented
or addressed. For example, if an article about Bernie Sanders presents an argument in favor of his proposal for free college, as well as the idea that others don’t think his plan is practical
because it would put too much of a burden on taxpayers, a counterargument is present.
4. Headline’s representativeness of the article Conceptual Definition- The degree to which a headline represents the subsequent
story is a headline’s representativeness. Operational Definition- A headlines representativeness of an article can be measured
by the positive and negative syntax used in the headline and article. Positive congruency/representativeness will have a matched tone between the headline and article.
x=0 (Negative Congruency) A headline with negative congruency to an article about Bernie Sanders’ proposal for free college will misrepresent the body of the text. For example, if a headline says that Sanders’ proposal of free college increases taxes, while the actual article says nothing about a rise in taxes, the headline is negatively congruent to the article. The same goes for the tone of the headline. If the article has a positive tone while the headline is more negative in nature, negative congruency is present.
y=1 (Positive Congruency) A headline with positive congruency to an article about Bernie Sanders’ proposal for free college will accurately represent the entirety of text in the article. For example, when a headline mentioning the alleviation of student debt from free college is followed up by text denoting the same idea, positive congruency is present; the same goes for tone, as long as there is consistency between the headline and the article. For example, whether an article criticizes or supports Sanders and his plan, as long as the tone of the headline matches the tone of the article, there is positive congruency.
5. Application of Statistics (Budak, 2016) Conceptual Definition- The application of statistics is when quantitative
data is used to analyze a particular argument. Operational Definition- The application of statistics in an article can be measured by the degree to which it is used to support or criticize an argument. It
is often the case that “statistics are disproportionately used to criticize one side.”(Budak, 2016)
x=0 (Unequal Application of Statistics) An unequal application of statistics will be present when an article uses quantitative data to only support or only criticize Bernie Sanders’ proposal of free college. For example,
an article with an unequal application of statistics may use quantitative data to show how free college for everyone would take away money from schools, while failing to show contrasting data depicting the financial benefits for college students.
y=1 (Equal Application of Statistics) An equal application of statistics will be present when an article uses quantitative data to analyze both the issues and benefits with Bernie Sanders’ proposal for free college. For example, an article with an equal application of statistics may use quantitative data to show how students benefit from a tuition reduction, while also showing quantitative data that depicts the burden taxpayers would face with a free college solution.
Coding Spreadsheet
Write each variable name in the column below (use an 8 character-or-less abbreviation of this variable name)
News Story Title positvty hdlnvalnc contrarg hdlnrep stats
An unworkable free-tuition plan
0
0
0
1
0
The false hope of free college
0
0
0
1
0
Sander’s idea of free tuition deserves an A
1
1
0
1
0
Clinton Adopts a Sanders Idea in Tuition Plan
1
1
1
1
1
Works Cited
Budak, C., Goel, S., Rao, J. M. (2016). Fair and balanced? Quantifying media bias through crowdsourced content analysis. Public Opinion Quarterly, Supplement(80), 250-271 doi:10.1093/poq/nfw007 Covert, T., Wasburn, P. (2007). Measuring media bias: A content analysis of time and newsweek coverage of domestic social issues, 1975–2000*. Social science quarterly, 88(3). Retrieved from
https://blackboard.cornell.edu/bbcswebdav/pid-3136949-dt-content-rid-8521507_1/courses/3837_2016FA/ Covert%20Wasburn%202007.pdf
Entman, R. (2008). Media framing biases and political power: Explaining slant in news of campaign in 2008.
Journalism, 11(4), 389-408. Retrieved from https://blackboard.cornell.edu/bbcswebdav/pid-3136949-dt-content-rid-8521506_1/courses/3837_2016FA/ Entman%202010.pdf
Articles Coded: An unworkable free-tuition plan The Washington Post August 6, 2016 Saturday The false hope of free college Washington Post Blogs February 23, 2016 Tuesday 12:00 PM EST http://www.latimes.com/politics/la-pol-sac-skelton-bernie-sanders-college-20160509-story.html Clinton Adopts a Sanders Idea in Tuition Plan The New York Times July 7, 2016 Thursday