The Hyperperception Model: What happens when we watch others online?

Carpenter & Spottswood. JoCTEC 2021 4(2), pp. 58-81

DOI: 10.51548/joctec-2021-010

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58

JoCTEC: Journal of Communication Technology (ISSN: 2694-3883)

Extending the Hyperpersonal Model to

Observing Others: The Hyperperception

Model

Christopher J. Carpentera and Erin L. Spottswoodb

aWestern Illinois University, Macomb, Illinois, USA; bPortland State University,

Portland, WA, USA

Correspondence: [email protected]

Abstract

Much of our Social Network Site (SNS) and associated mobile application use

involves observing and interpreting other people’s online presentations and

interactions. This paper proposes an extension of the hyperpersonal model

(Walther, 1996), called the hyperperception model, which can be used to

explain and predict the potential psychological and relational effects that

result from observing other people interact on SNSs and mobile apps. In this

new model the observer of other people’s online interactions is the focus

rather than the original hyperpersonal’s focus on the dyad. Hyperperception

effects occur when an observer perceives higher intensity in others’ SNS

interactions than those observed perceive. Following the hyperpersonal model,

this extension identifies channel, sender, receiver, and feedback loop

components that encourage hyperperceptions of others’ relationship by

observers on SNSs. Applications to a variety of interpersonal phenomena are

discussed.

Keywords: social networking sites, social media applications, hyperpersonal model, interpersonal relationships, loneliness, friendships, romantic

relationships

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Published by the Communication Technology Division of the Association for Education in Journalism and Mass Communication The Association for Education in Journalism and Mass Communication

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Introduction

Many people split their online time between interacting with people

directly and observing other people’s interactions (Leiner et al.,

2018) at least partially because communication technologies such as

Social Network Sites (SNSs) and their associated mobile

applications make other people’s interaction more accessible,

persistent (Ellison & Vitak, 2015), and associable (Fox & McEwan,

2017; Rice et al., 2017) than older direct messaging applications or

chat rooms did in the past. Thus, observation and even rumination

over other people’s SNS interactions is now possible and a popular

way to use these technologies. The purpose of this paper is to

present and explicate the hyperperception model, a model that

makes predictions about how observing others’ interact on SNSs can

cause inaccurate perceptions of the interactions being appraised and

also about the observed interaction partners’ relationships.

A hyperperception occurs when an observer perceives more

intensity between interaction partners the observer sees online than

the interaction partners themselves perceive. For this model,

“intensity” refers to a class of relational variables including intimacy,

closeness, similarity, tie strength, emotional involvement, and trust.

Although people make misattributions about the intensity of others’

relationships offline as well, the purpose of this model is to identify

when such misattributions are more or less likely to occur in online

environments. The same cognitive appraisals and misattributions

may occur offline, but our focus is on how and when they can occur

online. The model indicates four key components of observing others

in the SNS environment that can increase the likelihood of

hyperperception. The model focuses on the perceptions of an

observer, the channel the observer uses to make their appraisal, an

observed sender who the observer is motivated to observe, and one

or more observed receivers who interact with the observed sender in

online environments in which the observer may see the interactions.

This model extends the classic hyperpersonal model (Walther, 1996)

but switches focus from the perceptions of the interaction partners

themselves to the perceptions of an observer of a pair of interaction

partners. This new model is meant to complement the existing

model, and capture phenomena where observing other people

interact online can lead to a variety of offline interpersonal effects.

It is important that scholars attempt to develop models and theories

that can be used to help explain and predict some of the effects of

SNS observation given these technologies’ prevalence

internationally. The hyperperception model proposed in this paper

seeks to explain some of those effects by unifying some of the past

phenomenologically similar but often theoretically ungrounded

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research. In addition, the new model could be used to predict when,

how, and why SNS observations of others’ interactions can impact a

user’s psychological well-being as well as their personal

relationships as a consequence of inaccurate impressions of others’

relational intensity. Watching those we are close to interact with

others on SNSs may have profound psychological and interpersonal

effects such as loneliness (Frison & Eggermont, 2017), jealousy (Utz

et al., 2015), and other relational problems (Fox, 2016). This model

can contribute to understanding some of the reasons such effects

occur.

First, this paper will summarize the classic hyperpersonal model

followed by an explication of the proposed extension: the

hyperperception model. This paper will then suggest a few empirical

applications, identify boundary conditions, and conclude with the

hope that others may find the model useful for making unique

predictions about SNS use.

The Hyperpersonal Model

To understand the hyperperception model we must first revisit its

robust predecessor: the hyperpersonal model. The hyperpersonal

model (Walther, 1996) argues there are four components of online

communication that can create conditions under which

hyperpersonal relationships can develop, i.e. a particularly intense

online-only relationship. The first component focuses on the channel.

In the original description of the model, Walther (1996) described

how interacting via CMC 1) constrains the number of nonverbal cues

that are typically available during face-to-face (FtF) interaction as

well as 2) enable interaction partners more time to reflect, compose,

send, and interpret each other’s messages. So long as users

perceive that they can take advantage of these aspects of a

communication technology, they may present, interpret, and

communicate in ways that can lead to the development of a

hyperpersonal relationship between interaction partners.

Another important component of the channel is the social norms

users attempt to abide by when interacting with others via that

channel. Walther (1992; 1996) highlights how users must be

motivated to develop social relationships via CMC before engaging

in potentially hyperpersonal interactions with other users on that

channel. This motivation is likely influenced by the social norms

users associate with the channel they are using. A person will likely

be less motivated to use a channel for interpersonal interaction if they

think other users would perceive such disclosures as strange (e.g.,

LinkedIn, Plaxo). Given that motivation precedes hyperpersonal

processes (Walther, 2007), and motivation to engage in

interpersonal interaction depends on social norms (Burgoon, 1993),

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it follows that social norms should affect whether or not a user

perceives a channel is a good place to develop a (“hyper”)personal

relationship with another user of that channel.

The second component of the original hyperpersonal model focuses

on senders who take advantage of CMC channel affordances when

interacting with another person or people on that channel. The

original model focuses on channels that typically had mostly verbal

communication features (e.g., email, electronic bulletin boards, etc.).

As such, senders in these channels could be especially selective

about how they presented themselves to the receivers of their

messages because textual or verbal information is more “malleable”

and “subject to self-censorship” than nonverbal information (Walther,

1996, p. 20). SNSs allow senders to craft messages that include a

greater mix of verbal and nonverbal information. However, such

information is still somewhat more malleable than what is typical of

FtF interaction (Bazarova, 2012; Dumas et al., 2017; Hogan, 2010;

Qiu et al., 2012; Walther, 2007; Walther et al., 2015). When a sender

selectively self-presents because they are motivated to make the

best impression possible upon a receiver in hopes doing so will help

them cultivate a close relationship with the receiver, a hyperpersonal

relationship may develop between the dyad.

In order for hyperpersonal effects to take place, it is not enough for

senders to take advantage of the channel to selectively self-present;

the receiver component indicates that the receiver must make over-

attributions about the sender according to what the sender has

selectively presented on that channel. These over-attributions are

the third component of the hyperpersonal model (Walther, 1996). For

over-attributions to take place, receivers need to focus on the

sender’s disclosures that appeal to them and pay less attention to

disclosures that are less appealing or relevant to them (Bridges,

2012). In this way, the receiver paints an image of the sender in their

mind that is especially attractive to them. It is important to highlight

that whether or not the receiver makes over-attributions depends on

their own motivations as well as their perceptions of the channel

(Jiang et al., 2011). If a receiver perceives that the sender’s

messages or posts are directed at them, they may make over-

attributions that not only make the sender seem especially attractive

or interesting, but also encourages the receiver to feel that they

should selectively-self present in ways they perceive the sender

would appreciate.

Our interpretation of the hyperpersonal model is that these first three

parts specify the necessary conditions for a hyperpersonal

relationship. The fourth component of the model indicates how these

processes can build over time to enhance the basic perceptions that

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allow a hyperpersonal relationship to develop. In particular, if the

receiver responds to the sender’s selective self-presentation with

messages that are similar in tone, affect, intimacy, and topic, it is

possible that a feedback loop, the fourth component of the

hyperpersonal model, will start where the sender and receiver

exchange messages that confirm each other’s positive, perhaps

even idealized perceptions of their interactions as well as their

relationship. In this cycle of behavioral confirmation, each person is

increasingly expecting higher quality behavior and more positive

cues from the other. Each then responds to those expectations to

produce more positive behavior. And thus, CMC provides users with

the potential to forge hyperpersonal connections.

The Hyperperception Model

The four key components of the hyperpersonal model will be used to

structure the hyperperception model’s explanation of when and how

observers of others’ interactions on SNSs sometimes perceive those

interactions as more intense than those observed would report. The

hyperperception model parallels the key aspects of the

hyperpersonal model, but switches emphasis from sender-receiver

dynamics to the psychological and relational aspects of the observer

of two or more interpersonally relevant interaction partners. We

chose to make this model an extension of the hyperpersonal model

because we believe the perceptual processes that make a

relationship feel particularly intense online (a hyperpersonal

relationship) are similar to the processes that make a relationship

observed online appear particularly intense.

In the hyperperception model, the person who the observer is

motivated to observe is labeled the observed sender to indicate that

the observer is especially motivated to observe one SNS user’s

interactions. It is the sender’s interpretation of the observed

interactions that takes precedence in determining if hyperperception

has taken place because the observer is most interested in the extent

to which the observed sender believes the observed relationship is

intense. And, similar to the traditional distinction between sender and

receiver, there may be multiple important observed receivers for

whom the observer believes the sender is tailoring their messages.

Additionally, the observer is to other people sometimes a sender and

to others a receiver. But the model seeks to simplify the situation into

the observer, observed sender, observed receiver(s) roles to permit

theorizing about hyperperception by the observer.

It is important to note here that although we are using the terms

observed sender and observed receiver to maintain consistency with

the hyperpersonal model, similarly to that model, this model

recognizes that the distinction between observed sender and

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observed receiver is artificial. The distinction is adopted to allow

consistent terminology rather than to endorse a static model of

communication. Communication is ongoing such that multiple parties

are usually in a process of sending and receiving messages.

Channel Component

Just as the original hyperpersonal focused on aspects of CMC that

allowed for the development of hyperpersonal relationships (Walther,

1996), the channel component of the hyperperception model focuses

on aspects of the channel that allow observation of others’

interactions. The first key component of the hyperperception model

is that the channel must make at least some people’s interactions

accessible, persistent, and associable. These three aspects of the

channel are typically referred to as affordances. Affordances are a

multifaceted construct, but for this paper, affordances are defined as

what a person thinks they can do as well as what they think they

should do with communication technology based on their own needs

and wants, what they think the channel is for, and how they perceive

others use the same channel (Ellison & Vitak, 2015). Accessibility,

persistence, and association are all affordances often attributed to

SNS channels (Fox & McEwan, 2017; Rice et al., 2017). The

following definitions are specific to how they apply to the

hyperperception model. First, accessibility is the perception that one

can easily receive and review others’ messages or posts on SNSs.

Second, persistence is how long a message, post, or conversation

remains accessible and visible on a SNS. Third, association is the

perception that a post, reaction, comment, etc. is linkable or

traceable to a particular persona or identity (Rice et al., 2017). Given

that many SNSs make user’s posts and interactions associable to

corporeal entities with warrantable personas, observers can see and

access their partners’, friends’, and family members’ posts and

interactions so long as they persist on these technologies. As such,

channel affordances such as accessibility, persistence and

association can enable observational or surveillance behavior which

in turn affords the observer the ability to develop impressions of

others’ interactions and relationships.

The channel component builds off of research examining

observational phenomena that occurs on SNSs (Fox & Tokunaga,

2015; Marwick, 2012; Steinfeld, Ellison, & Lampe, 2008; Tokunaga,

2011; 2016). Work from these related lines of inquiry suggest that

part of the attraction of SNSs is their capacity to help people access

associable people’s behavior, interactions, and relationships as they

are posted and remain persistent on these channels (Fox et al.,

2014). For example, Joinson (2008) found that one of the main

reasons why people were drawn to the SNS Facebook was so that

they could engage in “virtual people watching” (p. 1034). Marwick’s

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(2012) interviews with SNS users also imply that people use these

channels to check-in on people they know and people they formerly

had close relationships with. SNSs allow observation of others’

interactions and many people take advantage of the affordance to

observe them.

Another key aspect of the channel that encourages hyperperception

are the norms encouraging posting “positive” content. Many people

who use SNSs seem to perceive that they should try to mostly post

about interesting topics, happy emotions, celebratory events, and

flattering pictures (Reinecke & Trepte, 2014; Spottswood & Hancock,

2016; Utz, 2015; Waterloo et al., 2018; Zhao et al., 2008). This is

known as the “positivity bias,” the perception that people should post

positive content and refrain from posting negative content on their

SNS profiles or accounts (Utz, 2015). As such, interactions the

observer sees between people on an SNS are likely to be peppered

with affirming or agreeable language, emoticons/emojis, and other

cues that imply that the interaction partners like each other. The more

interaction partners interact within such norms on an SNS, the more

an interested observer will view them discussing similar types of

topics and conclude they have a lot in common. This type of

interaction would suggest to the observer that the people they are

observing sometimes delve deep into each other’s interests when

they interact on SNSs, suggesting that they are developing or have

developed an especially close or intimate relationship. Moreover, if

the interaction partners have more observable interactions about a

variety of different topics where they both adhere to politeness and

positive posting norms, the observer might begin to perceive that the

observed pair seem to like a lot of the same things and as such must

like each other as well. Breadth and depth of topics discussed

between interaction partners is associated with interpersonal

intimacy (Altman & Taylor, 1973). As such, the positivity bias may

lead interaction partners to interact in ways that suggest they are

interpersonally close on SNSs even though they are just adhering to

the posting norms they attribute to these platforms. If an observer is

more focused on the people interacting versus the norms they

attribute to an SNS, they may perceive the interactions they observe

are indicative of relational closeness even though those they are

observing would not report that they are close with each other.

Observed Sender Component

The second key component of the hyperperception model indicates

that hyperperception effects are more likely if the observer is a)

especially motivated to observe the interactions of a particular

person on the SNS (observed sender) and b) also perceives that said

observed sender is selectively self-presenting to one or more specific

people using the same SNS. This dual aspect of the second

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component pulls from traditional interpersonal literature as well as

the claims made by the hyperpersonal model regarding sender’s

strategic use of a channel’s features to selectively self-present

(Walther, 1996).

There are a variety of potential motives for observing others’

interactions in SNS, which then in turn motivates observation of the

observed receivers they interact with as well. In general, people are

often interested in knowing about the strength of other people’s

relationships (Dillard, 1987; Rusbult et al., 2000). Moreover, people

in close relationships tend to compare the strength of their close

relationships against the strength of their close ties’ relationships

with other people (Guerrero & Andersen, 1998; Knobloch, Solomon,

& Cruz, 2001). This appraisal phenomena not only occurs offline but

online as well (Bevan, 2017), perhaps because of the affordances

that make others’ interactions accessible, associable, and persistent.

In the SNS context, research demonstrates that people are

motivated to observe their current romantic partners in SNSs when

they feel low satisfaction (Tokunaga, 2016) or when they have less

power in the relationship (Samp & Palevitz, 2014). They also observe

old interactions between their romantic partners and their partners’

ex-partners (Frampton & Fox, 2018). There is also evidence people

are motivated to observe their own ex-partners on SNSs (Tong,

2013). In a non-romantic context, people observe others on SNSs

just to reduce their uncertainty about those people (Antheunis et al.,

2010). Of course, people vary in the extent to which they are so

motivated to carefully observe others online but the greater that

motivation, the greater the likelihood of hyperperception effects. The

motives for observing may vary, but the hyperperception model

indicates that when such a motive exists, hyperperception becomes

more likely.

Hyperperception effects are also more likely when the observer

perceives that the observed sender is intentionally and positively

interacting with one or more particular other users of the SNS (the

observed receiver).When the observer perceives that the observed

sender is intentionally using an SNS to publicly (and perhaps also

privately) interact with another person, the observer may try to

access the observed sender’s interactions with that particular other

person and then compare their relationship to the observed sender

against their perceptions of the relationship between the observed

sender and the other person. For example, imagine an observed

sender posts a flattering post about themselves on Facebook. Many

people “like” it, a few people leave positive comments. Then the

observed sender “likes” and leaves replies of gratitude in response

to one of the comments. The commenter (who may become the

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observed receiver) replies affectionately, and thus begins a chain of

public interactions between the observed sender and commenter.

In situations where observers have a relational connection with one

of the members of the observed pair (e.g., a friend, family member,

romantic partner etc.), observers may begin to wonder how much the

person they are connected to (the observed sender) is interested in

the other less well known SNS user (the observed receiver). If the

observer has doubts about their own relationship with the observed

sender, they may begin to compare themselves to the observed

receiver. If the observer begins to make unfavorable comparisons

between themselves and the observed receiver, and worry that the

observed sender is justified in being drawn to the receiver, they may

start to worry that the observed sender is pursuing or developing a

relationship with the observed receiver. According to Festinger’s

(1954) social comparison theory, people sometimes try to determine

their value relative to another person according to what they deem is

socially or culturally attractive and appropriate. Frampton and Fox

(2018) noted that although self-presentations on SNSs may not be

targeted at a particular observer, that observer might still use others’

positive self-presentations to make unflattering social comparisons

to themselves.

Observed Receiver Component

The third component focuses on how well the observer knows the

observed receiver and is able to contextualize the observed

receiver’s SNS posts, especially the observed receiver’s interactions

with the observed sender. In the original hyperpersonal model, the

receiver had to over-attribute the sender’s self-presentation and

thereby perceive other positive traits because the receiver could not

gather additional information face-to-face (Walther, 1996). In the

hyperperception model, the observer makes over-attributions

concerning the intensity of the observed pair’s relationship because

the observer cannot observe them offline or access other

contextualizing information. Although such misattributions can occur

offline, the point here is that the substantially lower amount of

contextualizing information available in the SNS environment make

them substantially more likely. Having less, little, or no personal or

social history with the observed receiver of the observed sender’s

SNS reactions, tags, and comments may hinder the observer’s ability

to contextualize the interactions between the observed pair. If the

observer knew that the observed receiver was just as friendly with

others on SNSs besides the observed sender, the observer may not

perceive as much relational intensity between the observed pair.

This pattern may also hold true for additional observed receivers,

what is key to a hyperperception effect is the inability for the observer

to be able to contextualize the observed receiver(s) interactions with

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the observed sender (i.e., the person the observer is motivated to

observe).

One key cause for the observer’s inability to contextualize the

relationship between the observed sender and the observed receiver

is that the observer is constrained to a SNS channel for observing

their interactions. This constraint is important for several reasons.

First there are substantially fewer nonverbal cues in this channel to

provide evidence that the observed pair’s interactions, while friendly,

are not indicative of an intense relationship. Without the nonverbal

immediacy cues such as proximity and positive facial expressions

that would be available to the observer who saw that pair of people

interacting offline (Andersen, Andersen, & Jensen, 1979), the

observer must rely on what are mostly verbal cues and a few

nonverbal cues (pictorial, graphic, chronemic, etc.) available in the

SNS environment. As will be seen below, these cues may appear

more positive than they might offline. In some cases, the positivity

expressed on an SNS is reflective of actual relational intensity, but

our position is that SNSs can make some relationships appear more

intense than they are to those involved.

Secondly, when the observer is assessing the quality of the

interactions between the observed sender and observed receiver,

the same channel affordances the hyperpersonal model identified

that allow a particularly positive self-presentation may make it seem

as though the observed receiver possesses a great deal of

interpersonal value. When the observer is constrained to perceiving

the receiver only in a CMC environment that allows careful self-

presentation, that receiver might appear particularly attractive. Thus,

constrained access may encourage the observer to perceive the

observed pair’s interactions as particularly intense and the observed

receiver as a particularly desirable person to interact with.

Third, if observation is constrained to an SNS, the norms of the

channel coupled with the motivations of the users (e.g., to adhere to

site or app norms) may leave the observer with a hyperperception of

the intensity of the observed sender relationship with one or more

observed receivers. Such possibilities are consistent with

correspondence bias in which people tend to attribute behavior to

individual dispositions rather than context (Gawronski, 2004). In

other words, people may know that the context encourages positive

interactions, but they are likely to make individual attributions for the

positive behavior they see on SNSs.

Feedback Loop Component

The fourth and final component of the hyperperception model is the

feedback loop. In the original hyperpersonal model (Walter, 1996)

the mutual positive expectations of each other’s behavior caused a

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feedback loop where the sender and receiver increased their positive

perceptions of each other. The channel, sender, and receiver

components of the original model set the stage and a feedback loop

heightened the effects. In the hyperperception model, the channel,

sender, and receiver components indicate when hyperperception is

likely and the feedback loop indicates how such perceptions can

grow over time. In the hyperperception model, the observer may find

“evidence” of increased intensity if the first three components are

met, which motivates further observation. Additional observation

may uncover further evidence of positive interactions and thus create

a feedback loop of observation causing an increasingly strong motive

to observe. This loop likely includes rumination about the “evidence”

uncovered. Some research suggests that similar rumination is

implicated in negative social comparison effects stemming from SNS

use (Feinstein et al., 2013). This component suggests a longitudinal

orientation to hyperperception effects such that they are expected to

increase over time, as long as the other three components remain

present. Such a feedback loop was suggested by Muise et al. (2009)

in the Facebook jealousy context, but the hyperperception model

extends that possibility to any type of interpersonal electronic

surveillance in which some sign of heightened relational intensity

spurs further surveillance.

However, it is possible to exit from such a feedback loop. For

example, if new information allows the observer to contextualize the

observed sender and observed receiver’s interactions the observer

might break out of the feedback loop. Alternatively, the sender and

receiver could stop interacting in the semi-public spaces of the SNSs

available to the observer. But as long as 1) the channel gives the

interpersonally motivated observer persistent access to profiles that

are linked to SNS posts and interactions, 2) the observed pair appear

to be targeting each other for particular attention, 3) the observer has

little to no connection or history with the observed receiver(s), the

feedback loop is predicted to strengthen hyperperception effects

over time.

These four key components of the hyperperception model can be

used to help explore why sometimes observers develop “hyper”

perceptions of an observed pair’s relationship according to what they

see displayed on SNSs. Although the hyperperception model does

focus on SNSs, it is possible that some of these effects occurred in

older CMC contexts. For example, users of an electronic bulletin

board or online community could see other people’s interactions on

the board (Baym, 1995). As such, members of the community could

develop hyperperceptions of other member’s relationships according

to the conversations they saw displayed on the community’s

discussion page. Yet, the ubiquity of SNSs has created a context

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where observation is common of other users who have particular

personal importance to the observer and the hyperperception model

was created to understand when observation could lead to

hyperperception.

Heuristic Value of the Hyperperception Model

We will now discuss the heuristic potential of the model for a variety

of research areas in CMC. Chaffee and Berger (1987) explained that

a good theory must offer, “heuristic provocativeness. Good theories

generate new hypotheses, which expand the range of potential

knowledge” (p. 104). The hyperperception model can be used to

empirically explore more detailed explanations for a variety of

phenomena researchers have uncovered involving social media.

Assessing Romantic Availability

Many users of SNSs use these services to determine if someone is

romantically available (Fox et al., 2013). Although, some SNSs allow

people to list themselves as “single,” some observers may attempt

to determine if there is a relationship between the person they are

interested in (i.e., an observed sender) and a potential rival (i.e., an

observed receiver) that exists regardless of “relationship status.”

Mod (2010) found that in addition to listing themselves publicly as “in

a relationship” people also show a variety of displays of affection with

their romantic partners on Facebook. It is possible that someone

looking for a romantic relationship with a particular user might over-

interpret the closeness displayed between an observed sender and

an observed receiver (i.e., “a perceived rival”) on an SNS. The

hyperperception model could be used to predict particular scenarios

that are likely to produce an impression of a growing or extant

romantic relationship. The observed receiver component predicts

that this perception would be especially likely if the observer is

romantically interested in the observed sender and is not able to see

the observed pair’s interactions on other channels, such as face-to-

face in which the romantic interest of the perceived rival (or lack

thereof) would be clearer. To be sure, sometimes the observations

will be accurate, but the model can indicate conditions when a false

positive will be more likely.

To study this possibility, researchers could experimentally vary

various created sample SNS interactions and participants could

assess the likelihood that the observed pair in the sample interaction

are likely romantically involved. For example, the sender component

would suggest that a relationship is more likely to be inferred if the

sender appears to be selectively self-presenting for a particular

receiver. If the sender posts a status update and has a long back and

forth interaction in the comments section on that update with one

user while not responding to the other comments on the status

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update, that might be taken as a sign of increased closeness.

Romantic Jealousy

Previous research indicates that seeing one’s romantic partner

interacting with potential rivals on Facebook can spur jealousy

(Carpenter, 2016; Muise et al., 2009). Yet the particular kinds of

observed interactions that spur such jealousy are not clear.

Spottswood and Carpenter (2020b; 2020c; 2020d) have found

evidence that some of the processes predicted by the

hyperperception model can explain when Facebook-related romantic

jealousy is likely to occur. In particular, the observed receiver

component suggests that, consistent with previous research,

someone seeing their romantic partner interacting with potential

rivals on Facebook can produce jealousy. But the hyperperception

model goes further and specifies that in the SNS context, seeing a

potential rival interacting with one’s partner is especially likely to

produce jealousy if that supposed rival is not known to the observer

offline. The observed receiver component predicts that without the

contextualizing information of seeing a lack of nonverbal flirting in

offline contexts, the positive online interactions of their romantic

partners with potential rivals not known offline will be likely to produce

hyperperceptions and then jealousy. Across several studies, the data

were consistent with that hypothesis, thus allowing an exploration of

greater depth into SNS-related jealousy. Additional research is

needed to determine if similar patterns will emerge in other SNSs

such as Instagram.

The hyperperception research in this area thus far has used surveys

that focus on the receiver component by examining the extent to

which observers who see unknown potential rivals interacting with

the observers’ romantic partners are more jealous than those who

see known potential rivals. But more research is needed to examine

the proposed causes of that difference. Do observers perceive their

romantic partners as acting more receptive to these unknown rivals?

Do the unknown rivals seem more interested in the partner than the

known rivals? Additional experimental work is also needed in which

the variables specified by the hyperperception model are varied and

participants are asked to indicate the extent to which hypothetical

interactions between their partner and others would cause them to

feel jealous. Samp and Palevitz (2014) provide a good example of

using hypothetical social media posts to assess relational impact.

Although a number of studies have explored SNS-related jealousy

(Bevan, 2017), the hyperperception model opens up new avenues of

research.

Friendship Jealousy

Similar dynamics may occur in the context of friendship jealousy.

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Although romantic jealousy has a broader evidence base (Bevan,

2013), there is some evidence that people can feel their friendship is

threatened by their friends developing new friendships with others

(Bevan & Samter, 2004; Parker et al., 2005). The hyperperception

model would predict that if an observer is able to use an SNS

(channel component) and is motivated (observed sender

component) to observe their close friend interacting with people the

observer does not know (observed receiver component), the

observer may conclude that their friend is developing or has

developed closer friendships with one or more other people. For

example, SNS observations that result in hyperperception effects

might produce friendship jealousy when two close high school

friends go to different colleges. One friend (observer) may observe

the other (observed sender) interacting with all sorts of exciting and

fun looking new people at their college (observed receivers) on

Instagram (channel). The observer may assume that their high

school friend has moved on from their old friendship after seeing

these SNS interactions, but in reality their friend from high school just

wants to appear sociable and is actually missing their old friend, the

person observing them online.

This scenario suggests the possibility of survey research of first-year

college students. They might be asked to focus on a close friend who

went to a different college or university than themselves. The model

would predict friendship jealousy would be positively related to the

extent to which the friend at a different college posted pictures of

themselves with their new college friends. Yet, if the friend confined

their Instagram activity to posting pictures with their mutual friends

while home for the weekend or other content, the observing friend

would be predicted to experience less friendship jealousy. Such

hypotheses could be tested with longitudinal survey research.

Post Breakup Observation of Ex-Partners

Without SNSs, people whose romantic relationships have just ended

often have little opportunity to observe their ex-partners. Sometimes

people “remain friends” and see each other socially. But SNSs offer

unprecedented opportunities to observe the ex-partner interacting

with others if the ex-partner is active on an SNS and they remain

connected on that SNS. Several studies have found that remaining

connected on SNSs can make it harder for people to move on in a

healthy way (Fox & Tokunaga, 2015; LeFebvre, Blackburn, & Brody,

2015; Lukacs & Quan-Haase 2015). We recently conducted some

follow-up survey research using the hyperperception model

(Spottswood & Carpenter, 2020a). The research literature suggested

that seeing evidence of the partner initiating a new relationship was

particularly likely to hinder recovery. The data were consistent with

the receiver component prediction that seeing the ex-partner

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interacting with potential new partners whom the observer does not

know would hinder recovery more than observing interaction with

people the observer does know. Being constrained to just Facebook

(in this case) likely produced a hyperperception effect and thus

created the impression that the partner was developing a new

relationship. Further research is needed to assess the mediators in

the causal chain between the frequency with which the partner

interacts with new unknown people and poor recovery from breakup.

Loneliness

Passive Internet Use (PIU), otherwise known as “consumption” of

online content, has been defined by Verduyn and colleagues (2017)

as “the monitoring of other people’s lives without engaging in direct

exchanges with others” (p.281). They may be intentionally seeking

information, but the term “passive” here indicates they are not

directly interacting with those they observe. Some research suggests

that PIU exacerbates feelings of loneliness and negative mood

states (Appel, Gerlach, & Crusius, 2016; Shaw et al., 2015; Yang,

2016). The hyperperception model would predict that PIU can

sometimes cause loneliness because some of this passive use is

likely spent observing one’s interpersonally relevant contacts’ SNS

interactions that do not include the observer.

Most people do not completely share their social networks with any

particular friend they have. Inevitably, their friends know people they

do not and have social interactions with people they do not. In the

SNS context, one has the ability to observe those interactions

(channel component), they will see their friends trying to make a

positive impression on others via their interactions on the SNS

(observed sender component), and many of those “other” friends will

be people the observer is not friends with (observed receiver

component). The positivity bias may make the observed sender’s

interactions with the observed receivers seem particularly positive

and even better than their interactions with the observer. All of this

could add up to the observer feeling as though they do not offer

enough social value to their friends relative to the

fun/attractive/interesting people they see their friend (the observed

sender) connected to on the SNS. These worries may result in or

exacerbate feelings of loneliness. Survey research could be used to

assess the extent to which these specific kinds of observations are

associated with loneliness.

Boundary Conditions

The hyperperception model includes some assumptions that indicate

potential boundary conditions for the new model. First, the original

hyperpersonal model identified processes in which the sender

comes to have a particularly positive view of the receiver and of their

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relationship when interacting in CMC. The hyperperception model is

similar in that it assumes observers perceive that those they are

observing interacting with each other on social media have positive

views of each other. What is different is that the observer is making

assumptions about the dyad interacting via CMC. Hyperperceptions

are more likely to occur when the observer interprets the positivity of

the observed sender and observed receiver towards each other to

indicate relational intensity. Yet, observers may not always interpret

those positive interactions to indicate intensity. Romantic partners,

for example, will sometimes have positive illusions about their

partner’s fidelity (Murray & Holmes, 1997) that might prevent them

from seeing their partner’s interaction with others in an SNS as

particularly intense, even if other observers would.

The hyperpersonal model assumes the observed dyad adhere to

positivity norms and engage in particularly positive interactions with

each other. If the observed dyad’s interactions are not perceived as

especially positive, hyperperception would be unlikely, even if the

components of the model suggest hyperperception would be likely.

Some CMC platforms are thought to be endowed with certain norms

that encourage people to post and interact in ways that reflect

positively on them and those they are interacting with (Reinecke &

Trepte, 2014; Spottswood & Hancock, 2016; Utz, 2015). Yet, not all

current SNSs encourage positivity and it is unclear if all SNSs of the

future will have that norm. It is possible that the hyperperception

model will not be useful for aspects of CMC or social media that

create opportunities to observe others’ interactions when positivity

norms do not exist. Additional research is needed to assess the

importance of this aspect relative to the other components.

In addition, the model currently focuses on positive interactions as

the driver of perceptions of relational intensity. But it is possible that

observing negative interactions may also contribute to

hyperperception effects. Some people do not post, make comments,

or leave replies frequently on SNSs; their use tends to be more

passive and observational. For such people sufficient motivation is

necessary to prompt a person to engage in active interactions on

SNSs. Observing two people frequently making the effort to interact

negatively on an SNS may lead the observer to assume that one or

both members of the dyad feel strongly about each other. However,

it is possible that the negative interactions have nothing to do with

the relationship between the dyad but are instead about the

interaction topic (e.g., political candidates). However, if the observer

thinks that the dyad is in a kind of fight, then they may hyperperceive

how emotionally invested one or both members of the dyad are in

that relationship because if they were not emotionally invested they

would not bother to interact so intensely. Additional empirical work is

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needed to assess this possibility as a type of hyperperception.

Constrained interaction forms the key part of the receiver component

of the hyperperception model. Yet, constrained interaction is a matter

of degree and kind. Although our efforts thus far to study the model

have focused on how well the observer knows the observed receiver

offline, it is possible that the observer will be able to find

contextualizing information elsewhere. Someone might be trying to

determine if a particular classmate (observed sender) is romantically

unattached and this observer sees that classmate interacting

frequently and positively with a coworker on Facebook. The observer

might Google the coworker and discover that coworker is getting

married later that week when the observer finds that coworker’s

wedding website. So, it is important for researching the model going

forward to consider the variety of potential sources of contextualizing

information that would reduce the likelihood of hyperperception. As

more contextualizing information can be found online about more

people, hyperperceptions may be less likely to occur.

The original hyperpersonal model specified conditions under which

an online-only relationship could become more intense than similar

offline interaction. There may be cases in which the perception of the

observer is not hyper because the observed relationship is actually

hyperpersonal. Such relationships may be less likely to form in the

social media environments we are focused on here, however. The

sender is less able to control the information the receiver has access

to so the ideal self-presentation is harder to create. For example,

Walther et al. (2009) found that people rely more on the comments

of others rather than someone’s self-presentation in social media for

impression formation. Walther et al. (2008) found that perceptions of

someone’s attractiveness can be affected by how attractive the

person’s friends appear to be who comment on the target’s wall.

These aspects of social media make the kind of careful self-

presentation required for a hyperpersonal effect less likely. But the

extent to which the sender can control their self-presentation could

create conditions under which perception of intensity is not hyper,

but accurate.

Finally, this model takes a rational actor rather than a technological

determinism perspective (Markus, 1994). The model assumes

people are able to make choices that increase or decrease their

likelihood of hyperperception. For example, the feedback loop

component describes how people can avoid the feedback loop by

seeking contextualizing information or even directly communicating

with the observed sender (Spottswood & Carpenter, 2020c). The

extent to which this rational actor approach rather than a more

technological deterministic approach is valid forms an additional

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boundary condition to the model. The observer might try to reduce

their active surveillance of the sender to reduce hyperperception

effects but an SNSs algorithm might continue to display interactions

between the observed sender and observed receiver. For example,

someone might sever a relational tie with an ex-partner within an

SNS but the SNS might continue to display their ex-partner’s

interactions with the observer’s friends. As long as one remains a

user of a given SNS, one’s choices can only reduce surveillance to

a certain degree.

Conclusion

The hyperperception model is an extension of the hyperpersonal

model and posits that aspects of the channel, observed sender,

observed receiver, and feedback loops contribute to exaggerated

impressions of the interpersonal or intimate nature of interactions

and relationships as they are displayed on SNSs. The hyperpersonal

model focused on an interaction pair’s perceptions of each other, but

the hyperperception model focuses on the observer of two people’s

interactions rather than interaction partners themselves, and is

meant to be applied to SNSs and associated mobile applications or

communication technologies that have similar affordances. This

expansion of the original hyperpersonal model makes several

contributions. The model represents a theoretical advance in

understanding the unique social surveillance environment created by

SNSs. Much of what people see across a variety of SNSs (e.g.,

Facebook, Twitter, Instagram, Reddit, etc.) are records of social

interactions. Never before have so many had so much access to a

semi-permanent chronicle of their friends’, family members’, or

romantic partners’ interaction behavior with other people.

Research using the hyperperception model can yield new insights

into the negative psychological outcomes of loneliness, romantic

jealousy, relational insecurity, and possibly other SNS social

phenomena not mentioned here. It is important to begin building

models and theories that can explain and predict how this unique

observer position affects our relationships and our lives both on

SNSs and beyond. The hyperperception model builds on the insights

of the original hyperpersonal model (Walther, 1996) and begins

exploring how new communication technology affect our perceptions

of ourselves, our relationships, and now more than ever, other

people’s relationships. Sometimes what observers perceive is not

hyper but actual, meaning that they are being excluded (e.g., fear of

missing out, FOMO), their friend is making new friends that supplant

their old friends, or that their romantic partner is flirting with someone

else. Yet, there is some evidence that there are times when the

perception of intensity is unfounded (Spottswood & Carpenter,

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2020c). The hyperperception model could help observers refrain

from seeing relationship intensity developing online that is not really

there and instead help them probe why they might be suspicious or

anxious to begin with. For example, rather than hyperperceiving their

friends are not including them or inviting them to events and

gatherings, they realize that the posts they are appraising include

events they would not be interested in anyway or happen to be

scheduled when they said they would not be available. This

perception correction could decrease feelings of FOMO, loneliness,

and social anxiety which speaks to the practical utility of the model.

As long as CMC includes environments in which others’ interactions

can be observed, this model will offer a useful way to explain and

predict how observing others’ online interactions affects people’s

views of themselves, their relationships, and their current, past, and

possible relational partners.

Christopher J. Carpenter (PhD, Michigan State University, 2010) is a professor in the Department of Communication at Western Illinois University. His research focuses on close relationships on social media, opinion leadership, and motivated reasoning. He has published over 50 peer-reviewed articles in academic journals and co-authored the persuasion textbook, "Critical Questions in Persuasion Research." commcarpenter.com Erin L. Spottswood (PhD, Cornell University, 2014) researches how people perceive and attempt to use information communication technologies to achieve their personal and professional goals. She has been featured in journals such as Journal of Computer-Mediated Communication, Current Opinion in Psychology, Computers and Human Behavior, and Behavior and Information Technology.

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References

Andersen, J. F., Andersen, P. A., & Jensen, A. D. (1979). The measurement of nonverbal immediacy. Journal of Applied Communication Research, 7(2), 153-180. https://doi.org/10.1080/00909887909365204

Appel, H., Gerlach, A. L., & Crusius, J. (2016). The interplay between Facebook use, social comparison, envy, and depression. Current Opinion in Psychology, 9, 44-49. https://doi.org/10.1016/j.copsyc.2015.10.006

Baym, N. K. (1995). The emergence of community in computer-mediated communication. In S. G. Jones (Ed.), CyberSociety: Computer-mediated communication and community (pp. 138-163). Sage.

Bazarova, N. N. (2012). Public intimacy: Disclosure interpretation and social judgments on Facebook. Journal of Communication, 62(5), 815-832. https://doi.org/10.1111/j.1460- 2466.2012.01664.x

Berger, C. R., & Calabrese, R. J. (1975). Some explorations in initial interactions and beyond: Toward a developmental theory of interpersonal communication. Human Communication Research, 1(2), 99-112. https://doi.org/10.1111/j.1468- 2958.1975.tb00258.x

Bevan, J. L. (2013). The communication of jealousy. Peter Lang.

Bevan, J. L. (2017). Romantic jealousy experience and expression and social networking sites. In N. M. Punyanunt-Carter & J. S. Wrench (Eds.), The impact of social media in modern romantic relationships (pp. 165-180). Lexington Books.

Bevan, J. L., & Samter, W. (2004). Toward a broader conceptualization of jealousy in close relationships: Two exploratory studies. Communication Studies, 55(1), 14-28. https://doi.org/10.1080/10510970409388603

boyd, d. (2010). Social network sites as networked publics: Affordances, dynamics, and implications. In Z. Papacharissi (Ed.), A networked self (pp. 47-66). Routledge.https://doi.org/10.4324/9780203876527-8

Bridges, J. C. (2012). The illusion of intimacy: Problems in the world of online dating. Praeger.

Burgoon, J. K. (1993). Interpersonal expectations, expectancy violations, and emotional communication. Journal of Language and Social Psychology, 12(1-2), 30-48. https://doi.org/10.1177/0261927x93121003

Carpenter, C. J. (2016). Romantic jealousy on Facebook. International Journal of Interactive Communication Systems and Technologies, 6(1), 1-16. https://doi.org/10.4018/ijicst.2016010101

Chaffee, S. H., & Berger, C. R. (1987). What communication scientists do. In C. R. Berger & S. H. Chaffee (Eds.), Handbook of Communication Science (pp. 99-122). Sage.

Dillard, J. P. (1987). Close relationships at work: Perceptions of the motives and performance of relational participants. Journal of Social and Personal Relationships, 4(2), 179-193. https://doi.org/10.1177/0265407587042005

Dumas, T. M., Maxwell-Smith, M., Davis, J. P., & Giulietti, P. A. (2017). Lying or longing for likes? Narcissism, peer belonging, loneliness and normative versus deceptive like- seeking on Instagram in emerging adulthood. Computers in Human Behavior, 71(1), 1- 10. https://doi.org/10.1016/j.chb.2017.01.037

JoCTEC: Journal of Communication Technology

Carpenter & Spottswood. JoCTEC 2021 4(2), pp. 58-81

78

Ellison, N. B., & Vitak, J. (2015). Social network site affordances and their relationship to social capital processes. In S. S. Sundar (Ed.), The handbook of the psychology of communication technology (205-227). Wiley. https://doi.org/10.1002/9781118426456.ch9

Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013). Negative social comparison on Facebook and depressive symptoms: Rumination as a mechanism. Psychology of Popular Media Culture, 2, 161-170. https://doi.org/10.1037/a0033111

Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117-140. https://doi.org/10.1177/001872675400700202

Fox, J. (2016). The dark side of social networking sites in romantic relationships. In G. Riva, B. K. Wiederhold, & P. Cipresso (Eds.), The psychology of social networking: Personal experiences in online communities (pp. 78-89). De Gruyter. https://doi.org/10.1515/9783110473780-009

Fox, J., & Anderegg, C. (2014). Romantic relationship stages and social networking sites: Uncertainty reduction strategies and perceived relational norms on Facebook. Cyberpsychology, Behavior, and Social Networking, 17(11), 685-691. https://doi.org/10.1089/cyber.2014.0232

Fox, J., & McEwan, B. (2017). Distinguishing technologies for social interaction: The perceived social affordances of communication channels scale. Communication Monographs, 84(3), 298-318. https://doi.org/10.1080/03637751.2017.1332418

Fox, J., Osborn, J. L., & Warber, K. M. (2014). Relational dialectics and social networking sites: The role of Facebook in romantic relationship escalation, maintenance, conflict, and dissolution. Computers in Human Behavior, 35, 527-534. https://doi.org/10.1016/j.chb.2014.02.031

Fox, J., & Tokunaga, R. S. (2015). Romantic partner monitoring after breakups: Attachment, dependence, distress, and post-dissolution online surveillance via social networking sites. Cyberpsychology, Behavior, and Social Networking, 18(9), 491-498. https://doi.org/10.1089/cyber.2015.0123

Fox, J., Warber, K. M., & Makstaller, D. C. (2013). The role of Facebook in romantic relationship development: An exploration of Knapp’s relational stage model. Journal of Social and Personal Relationships, 30(6), 771-794. https://doi.org/10.1177/0265407512468370

Frampton, J. R., & Fox, J. (2018). Social media’s role in romantic partners’ retroactive jealousy: Social comparison, uncertainty, and information seeking. Social Media + Society, 4(3). https://doi.org/10.1177/2056305118800317

Frison, E., & Eggermont, S. (2017). Browsing, posting, and liking on Instagram: The reciprocal relationships between different types of Instagram use and adolescents' depressed mood. Cyberpsychology, Behavior, and Social Networking, 20(10), 603-609. https://doi.org/10.1089/cyber.2017.0156

Gawronski, B. (2004). Theory-based bias correction in dispositional inference: The fundamental attribution error is dead, long live the correspondence bias. European Review of Social Psychology, 15(1), 183-217. https://doi.org/10.1080/10463280440000026

Guerrero, L. K., & Andersen, P. A. (1998). Jealousy experience and expression in romantic relationships. In P. A. Anderson & L. K. Guerrero (Eds.), Handbook of communication and emotion: Research, theory, applications, and contexts (pp. 155-188). Academic Press.

JoCTEC: Journal of Communication Technology

Carpenter & Spottswood. JoCTEC 2021 4(2), pp. 58-81

79

Hogan, B. (2010). The presentation of self in the age of social media: Distinguishing performances and exhibitions online. Bulletin of Science, Technology & Society, 30(6), 377-386. https://doi.org/10.1177/0270467610385893

Jiang, L., Bazarova, N. N., & Hancock, J. T. (2011). The disclosure–intimacy link in computer‐mediated communication: An attributional extension of the hyperpersonal model. Human Communication Research, 37(1), 58-77. https://doi.org/10.1111/j.1468- 2958.2010.01393.x

Joinson, A. (2008). Looking at, looking up, or keeping up with people? Proceedings of the twenty-sixth annual CHI conference on human factors in computing systems (pp. 1027-1036). https://doi.org/10.1145/1357054.1357213

Knobloch, L. K., & Solomon, D. H. (2002). Information seeking beyond initial interaction. Human Communication Research, 28(2), 243-257. https://doi.org/10.1111/j.1468- 2958.2002.tb00806.x

Knobloch, L. K., Solomon, D. H., & Cruz, M. G. (2001). The role of relationship development and attachment in the experience of romantic jealousy. Personal Relationships, 8(2), 205-224. https://doi.org/10.1111/j.1475-6811.2001.tb00036.x

Leiner, D. J., Kobilke, L., Rueß, C. & Brosius, H. B. (2018). Functional domains of social media platforms: Structuring the uses of Facebook to better understand its gratifications. Computers in Human Behavior, 83, 194-203. https://doi.org/10.1016/j.chb.2018.01.042

Markus, M. L. (1994). Finding a happy medium: Explaining the negative effects of electronic communication on social life at work. ACM Transactions on Information Systems, 12(2), 119-149. https://doi.org/10.1145/196734.196738

Marwick, A. E. (2012). The public domain: Social surveillance in everyday life. Surveillance & Society, 9, 378-393. https://doi.org/10.1016/j.chb.2018.01.042

Mod, G. B. B. A. (2010). Reading romance: The impact Facebook rituals can have on a romantic relationship. Journal of Comparative Research in Anthropology and Sociology, 1(2), 61-77.

Muise, A., Christofides, E., & Desmarais, S. (2009). More information than you ever wanted: Does Facebook bring out the green-eyed monster of jealousy? CyberPsychology & Behavior, 12(4), 441-444. https://doi.org/10.1089/cpb.2008.0263

Parker, J. G., Low, C. M., Walker, A. R., & Gamm, B. K. (2005). Friendship jealousy in young adolescents: Individual differences and links to sex, self-esteem, aggression, and social adjustment. Developmental Psychology, 41(1), 235. https://doi.org/10.1037/0012- 1649.41.1.235

Qiu, L., Lin, H., Leung, A. K., & Tov, W. (2012). Putting their best foot forward: Emotional disclosure on Facebook. Cyberpsychology, Behavior, and Social Networking, 15(10), 569-572. https://doi.org/10.1089/cyber.2012.0200

Reinecke, L., & Trepte, S. (2014). Authenticity and well-being on social network sites: A two-wave longitudinal study on the effects of online authenticity and the positivity bias in SNS communication. Computers in Human Behavior, 30, 95-102. https://doi.org/10.1016/j.chb.2013.07.030

Rice, R. E., Evans, S. K., Pearce, K. E., Sivunen, A., Vitak, J., & Treem, J. W. (2017). Organizational media affordances: Operationalization and associations with media use. Journal of Communication, 67(1), 106-130. https://doi.org/10.1111/jcom.12273

JoCTEC: Journal of Communication Technology

Carpenter & Spottswood. JoCTEC 2021 4(2), pp. 58-81

80

Rusbult, C. E., Van Lange, P. A., Wildschut, T., Yovetich, N. A., & Verette, J. (2000). Perceived superiority in close relationships: Why it exists and persists. Journal of Personality and Social Psychology, 79(4), 521-545. https://doi.org/10.1037/0022- 3514.79.4.521

Shaw, A. M., Timpano, K. R., Tran, T. B., & Joormann, J. (2015). Correlates of Facebook usage patterns: The relationship between passive Facebook use, social anxiety symptoms, and brooding. Computers in Human Behavior, 48, 575-580. https://doi.org/10.1016/j.chb.2015.02.003

Spottswood, E. L., & Carpenter, C. J. (2020a). Breaking up is hard to do, especially when Facebook won’t let you. Proceedings of the Social Media & Society Conference (pp. 30- 38). https://doi.org/10.1145/3400806.3400811

Spottswood, E. L. & Carpenter, C. J. (2020b). Facebook jealousy: A hyperperception perspective. Communication Quarterly, 68(4), 397-416. https://doi.org/10.1080/01463373.2020.1804959

Spottswood, E. L., & Carpenter, C. J. (2020c). The hyperperception model: How observing others on social media can affect people in close relationships. In R. A. Lind (Ed.), Produsing theory in a digital world 3.0: The intersection of audiences and production in contemporary theory (Vol. 3). Peter Lang.

Spottswood, E. L., & Carpenter, C. J. (2020d). The hyperperception model: What you don’t know can hurt you. International Journal of Interactive Communication Systems and Technologies, 10(1), 1-12. https://doi.org/10.4018/IJICST.2020010101

Spottswood, E. L., & Hancock, J. T. (2016). The positivity bias and prosocial deception on Facebook. Computers in Human Behavior, 65, 252-259. https://doi.org/10.1016/j.chb.2016.08.019

Steinfeld, C., Ellison, N. B., & Lampe, C. (2008). Social capital, self-esteem, and use of online social network sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29(6), 434–445. https://doi.org/10.1016/j.appdev.2008.07.002

Tandoc, E. C., Ferrucci, P., & Duffy, M. (2015). Facebook use, envy, and depression among college students: Is facebooking depressing? Computers in Human Behavior, 43, 139-146. https://doi.org/10.1016/j.chb.2014.10.053

Tokunaga, R. S. (2011). Social networking site or social surveillance site? Understanding the use of interpersonal electronic surveillance in romantic relationships. Computers in Human Behavior, 27(2), 705-713. https://doi.org/10.1016/j.chb.2010.08.014

Tokunaga, R. S. (2016). Interpersonal surveillance over social network sites: Applying a theory of negative relational maintenance and the investment model. Journal of Social and Personal Relationships, 33(2), 171-190. https://doi.org/10.1177/0265407514568749

Utz, S. (2015). The function of self-disclosure on social network sites: Not only intimate, but also positive and entertaining self-disclosures increase the feeling of connection. Computers in Human Behavior, 45, 1-10. https://doi.org/10.1016/j.chb.2014.11.076

Utz, S., Muscanell, N., & Khalid, C. (2015). Snapchat elicits more jealousy than Facebook: A comparison of Snapchat and Facebook use. Cyberpsychology, Behavior, and Social Networking, 18(3), 141-146. https://doi.org/10.1089/cyber.2014.0479

Verduyn, P., Ybarra, O., Résibois, M., Jonides, J., & Kross, E. (2017). Do social network sites enhance or undermine subjective well-being? A critical review. Social Issues and Policy Review, 11(1), 274-302. https://doi.org/10.1111/sipr.12033

Walther, J. B. (1992). Interpersonal effects in computer-mediated interaction: A relational

JoCTEC: Journal of Communication Technology

Carpenter & Spottswood. JoCTEC 2021 4(2), pp. 58-81

81

perspective. Communication Research, 19(1), 52-90. https://doi.org/10.1177/009365092019001003

Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication research, 23(3), 3-43. https://doi.org/10.1177/009365096023001001

Walther, J. B. (2007). Selective self-presentation in computer-mediated communication: Hyperpersonal dimensions of technology, language, and cognition. Computers in Human Behavior, 23(5), 2538-2557. https://doi.org/10.1016/j.chb.2006.05.002

Walther, J. B., Van Der Heide, B., Hamel, L. M., & Shulman, H. C. (2009). Self-generated versus other-generated statements and impressions in computer-mediated communication: A test of warranting theory using Facebook. Communication Research, 36(2), 229-253. https://doi.org/10.1177/0093650208330251

Walther, J. B., Van Der Heide, B., Kim, S. Y., Westerman, D., & Tong, S. T. (2008). The role of friends’ appearance and behavior on evaluations of individuals on Facebook: Are we known by the company we keep? Human Communication Research, 34(1), 28-49. https://doi.org/10.1111/j.1468-2958.2007.00312.x

Walther, J. B., Van Der Heide, B., Ramirez, A., Burgoon, J. K., & Peña, J. (2015). Interpersonal and hyperpersonal dimensions of computer-mediated communication. In S. S. Sundar (Ed.), The handbook of the psychology of communication technology (pp. 3- 22). Wiley Blackwell. https://doi.org/10.1002/9781118426456.ch1

Wang, J. L., Gaskin, J., Rost, D. H., & Gentile, D. A. (2018). The reciprocal relationship between passive social networking site (SNS) usage and users’ subjective well-being. Social Science Computer Review, 36(5), 511-522. https://doi.org/10.1177/0894439317721981

Waterloo, S. F., Baumgartner, S. E., Peter, J., & Valkenberg, P. M. (2018). Norms of online expressions of emotion: Comparing Facebook, Twitter, Instagram, and WhatsApp. New Media & Society, 20(5), 1813-1831. https://doi.org/10.1177/1461444817707349

Yang, C. C. (2016). Instagram use, loneliness, and social comparison orientation: Interact and browse on social media, but don't compare. Cyberpsychology, Behavior, and Social Networking, 19(12), 703-708. https://doi.org/10.1089/cyber.2016.0201

Zhao, S., Grasmuck, S., & Martin, J. (2008). Identity construction on Facebook: Digital empowerment in anchored relationships. Computers in Human Behavior, 24(5), 1816- 1836. https://doi.org/10.1016/j.chb.2008.02.012

Carpenter, C.J., & Spottswood, E.L. (2021). Extending the

hyperpersonal model to observing others: The hyperperception

model. Journal of Communication Technology, 4(2), 58-81. DOI:

10.51548/joctec-2021-010.