10
Media Choice and Selective Exposure
Silvia Knobloch-Westerwick, Axel Westerwick, and Daniel J. Sude
In an era of virtually inexhaustible choices of media channels and messages, the question of
what motivates individuals to attend to a particular outlet or type of content becomes especially
pressing. At least in developed countries, people are often inundated by a multitude of sources
around the clock. As several chapters in this volume report, a plethora of research has established
that media exposure shapes recipients’ views of the world, others, and themselves, with
both short and long-term eﬀects. Alongside emotional and attitudinal impacts, media exposure
aﬀects behaviors. Yet a pivotal threshold, before media exposure can impact recipients, is selection.
With ample messages available, most mediated communication is a matter of choice. Typically,
individuals choose what messages they attend to and thus engage in selective exposure.
This chapter will clarify what drives such selective exposure.
First, we will review technological changes that shape media choice environments and then differentiate
layers involved in media choice. Terminology connected to selective exposure will be
established next. The research review will diﬀerentiate three traditions before focusing on speciﬁc
concepts and evidence. Finally, we oﬀer some concluding remarks and future research suggestions.
Technology Shaping Media Choice Environments
An unprecedented increase of media channels occurred with the introduction of cable and satellite
television. Zapping between TV channels became a focus of research in the 1980s (e.g.,
Becker & Schönbach, 1989). Abundant channels and remote controls not only allowed people
to avoid commercials but also to choose from a much greater variety of content. Moreover,
recording media content facilitated time-shifting in consumption of programming, as well as
skipping segments.
The internet era then led to a skyrocketing increase of available media content. Easy online
content generation and dissemination now make an enormous variety of sources accessible,
while search engines and ﬁltering technologies (e.g., newsfeeds) help to focus users’ attention.
Sophisticated algorithms provide content suggestions with the presumably best ﬁt to the entered
search terms; they inﬂuence consumers’ exposure to online content signiﬁcantly but may present
an incomplete, biased picture of a given topic. Additionally, modern websites guide
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Media Choice and Selective Exposure • 147
consumers’ selections by using cookies to store browsing history and user preferences for content
customization and personalization (Kang & Sundar, 2016). With the appearance of social
media, user generated content increased dramatically, starting with blogs and wikis, followed by
Myspace, Facebook, YouTube, Twitter, Instagram, and the like. Through the mix of usergenerated
content and messages from media organizations, the internet today provides fewer
orientation points for the user regarding who is actually responsible for content and how content
may have been altered. Understanding how users choose mediated content is more pressing
than ever in light of these technological changes.
To illustrate how accessing diﬀerent media leads to abundant multi-layered choices, it is
helpful to specify how content selection happens on diﬀerent layers. On the top layer, consumers
choose from channels like TV, radio, internet, magazines, or newspapers. They can even
use several at the same time, by just shifting their attention. On the next layer, users exert
choices within a medium, for example, by surﬁng diﬀerent websites, switching TV or radio
channels, or browsing diﬀerent newspapers. On the third level, they can select from diﬀerent
oﬀerings on the same website, pick out particular TV shows, or read just one speciﬁc newspaper
article or a speciﬁc newspaper section. On the lowest level, users may select within a particular
article or show, for instance by reading select paragraphs of some of the articles in a newspaper
or watching select scenes of a TV show.
A key technological development that signiﬁcantly changes media content use and selection is
that internet technologies integrate almost all of the content that the other outlets traditionally provided
through separate media. Through digitization of TV and radio—as well as online versions of
newspapers, books, journals, videos, and music—most content is increasingly disseminated through
the internet (Lugmayr & Dal Zotto, 2016). Thus, content selection and consumption are increasingly
inﬂuenced by online display features like consumer ratings, likes, reviews, and tailored ads,
intertwined with the content, as well as big-data algorithms for customization and personalization.
Terminology of Selective Exposure and Media Choice
As numerous terms have been used regarding media choice phenomena, we ﬁrst want to clarify
some terminology. Historically, the term selective exposure was ﬁrst used by Lazarsfeld, Berelson,
and Gaudet (1948) to describe that, before an election, media users exhibit a preference for
messages and outlets that convey a stance in line with their own political views. Yet its contemporary
use is much broader: Selective exposure relates to individuals’ selections of mediated
content and can be conceptualized on an aggregate or an individual level; it denotes “any systematic
bias in audience composition for a given medium or message, as well as any systematic
bias in selected messages that diverges from the composition of accessible messages” (KnoblochWesterwick,
2015a, p. 3).
For example, when Kris spends 60 minutes on TV while having access to ten channels, she
is unlikely to spread this time equally across channels and may spend 50 minutes with one of
them. This example illustrates a bias in selected messages: Kris may spend the hour mostly with
a news or a comedy channel. Users almost always exhibit systematic bias in selecting media
messages. Such individual selective exposure decisions result in systematic biases in audience
composition on the aggregate level; for instance, men may be more likely than women to tune
into sports channels, which is exhibited in a systematic bias in audience composition when
sports channels viewers are predominantly male. Why such tendencies exist is at the heart of
selective exposure research.
148 • Silvia Knobloch-Westerwick et al.
There are numerous ways and units of expressing selective exposure patterns—for instance,
time portions, choice frequencies, or choice proportions—and the most suitable way of capturing
the phenomenon depends on the theory and hypotheses under consideration. Investigations
may look at speciﬁc choices of mediated messages observed in a given situation, as opposed to
generalized preferences for types of messages. An example of a media choice would be that
Morgan chose to watch the movie Annie yesterday, whereas a preference is a pattern of several
choices wherein Morgan usually prefers to watch musical movies when encountering them as
an option. Yet a preference is not equivalent to a habit: Morgan watches the news every day,
such that these daily choices accumulate to a habit. But her preference for musical movies
might only play out when she sits down a few times a year to watch a movie through an ondemand
service.
Related to the notions of choice versus preference, an investigation may examine what situational
circumstances render a particular media choice more likely or, on the other hand, what
dispositional factors (i.e., traits) foster particular media exposure choices. Either way, any investigation
of selective media exposure will rely on some content characterization of media channels
or messages (e.g., choosing sitcom vs. drama, or a violent vs. a non-violent video game, or
classical vs. popular music). It is important to note that many studies of actual selective media
exposure are simultaneously interested in situations, dispositions, and content; for instance,
exploring if people who are generally more aggressive (disposition) are more likely to choose
violent videos (content) after being provoked (situation), or whether men are more likely than
women (disposition per gender) to choose negative online news (content) when they think they
will get to retaliate against a provoker (situation) (Knobloch-Westerwick & Alter, 2006; O’Neal &
Taylor, 1989).
All these elaborations serve to answer the question we posed initially: What drives selective
exposure? In conceptual terms, scholars seek to understand motivations underlying media
choices. The term motivation denotes an internal process within an individual that causes goaldirected
behaviors, such as selecting a media message as a behavior to accomplish a certain
goal. Related terms are needs that bring media use about or gratiﬁcations that individuals seek
to derive from media use (Palmgreen & Rayburn, 1982); in fact, the terminology is closely intertwined
with diﬀerent theoretical perspectives and methodological traditions, as the next section
will clarify.
Research Traditions Regarding Selective Media Exposure
Uses and Gratiﬁcations (U&G) Approach
Herzog (1944) conducted the ﬁrst study on what drives media users to attend to mediated messages.
It took decades, however, until an elaborate research paradigm emerged with the uses
and gratiﬁcations (U&G) approach. For instance, Katz and Foulkes (1962, p. 377) noted “there
is a great need to know what the people do with the media,” taking a contrasting view to the
then-predominant media eﬀects research, and highlighted selective exposure as a pivotal phenomenon
because “viewers, listeners and readers ultimately determine the content of the media
by their choices of what they will read, view, or hear.” In the 1970s and 1980s, the U&G
approach ﬂourished. Scholars generally agreed on the importance of disentangling the so-called
needs that the audience members aimed to fulﬁll with media use, and what gratiﬁcations they
sought through media exposure. These terms are closely connected with research characterized
Media Choice and Selective Exposure • 149
by the following: Survey respondents rated statements meant to capture why they attended to
particular messages, programs, or channels. For example, Rubin (1983) asked participants to
indicate the reasons they watched television with statements such as “Because it relaxes me”
and “Because it helps me learn things about myself and others” in a survey, based on a ﬁvepoint
scale ranging from “not at all” to “exactly.” As typical for the U&G approach, Rubin
(1983) then extracted viewing motives such as habit, pass time, and escape among others via
factor analysis.
This research approach connects with a key proposition of the U&G approach: Media users
are thought to be aware of what motivates their use (Blumler & Katz, 1974), which justiﬁes selfreport
survey questions. Undoubtedly, the U&G approach inspired a large body of research with
hundreds of studies (Sundar & Limperos, 2013). However, certain criticisms may explain why its
inﬂuence diminished: The self-report measures used to capture media use motivations rely on
a level of introspection that has often been questioned (e.g., Zillmann, 1985). Take, for example,
a teenager who chooses to watch a war tragedy that makes him cry. When presented with
prompts such as “to pass time” or to “learn new information,” the teen might indicate a high level
of agreement with these suggested gratiﬁcations. But possibly, he picked the movie—consciously
or not—to see soldiers in deplorable circumstances, hoping to feel better about his own minor
strains. Also, U&G studies relied on cross-sectional, correlational designs that cannot establish
causality. They usually did not include media exposure measures and merely used self-reports on
motivations, disregarding actual behavior. These methodological aspects distinguish this tradition
from the approaches explained next.
Dynamic-Transactional Models
In contrast to the U&G tradition, approaches under the umbrella of dynamic-transactional
models do not rely on self-reported media use motivations but capture media exposure in some
fashion to infer motivations and use panel survey designs. A dynamic-transactional view was
ﬁrst introduced by Früh and Schönbach (1982) who drew on media exposure measures to represent
use motivations in media eﬀects analyses. In their DTA (dynamic-transactional
approach), inter-transactions denote imagined or actual interactions between communicator
and recipient, which can inﬂuence both parties. Indeed, in the current era where users generate
much of the content available online, the inter-transactions may be more important than in the
1980s when the model was developed, because user-generated content necessitates the conceptualization
of these speciﬁc transactions even more so than the traditional mass media context.
Furthermore, intra-transactions pertain to the interplay of psychological characteristics of users
(i.e., activation level, aﬀect, attention, interest, knowledge), which also change as a result of
receiving media messages.
The DTA diﬀers from broader media eﬀects models, as well as from the uses and gratiﬁcations
view, in that neither media nor users’ motives are considered the key cause of eﬀects. Whereas
traditional media eﬀects models postulated that media exposure causes eﬀects (e.g., McQuail,
1994) and the uses and gratiﬁcations approach (e.g., Blumler & Katz, 1974) emphasized that
users’ motivations bring about media eﬀects, the DTA married these two positions and suggested
that both media and users’ characteristics and motives instigate media eﬀects in a dynamic, ﬂuctuating
interchange. Yet the DTA did not detail more speciﬁc motivations for selective exposure.
Recent models of selective media use and subsequent eﬀects reiterate central propositions of
the DTA. Slater’s (2007) reinforcing spirals model (RSM) also emphasizes the dynamic nature
150 • Silvia Knobloch-Westerwick et al.
of processes in which attitudes are created and maintained through media use. The term attitudes
is used in a broad sense and includes durable perceptions of one’s own lifestyle, social
identity, religion, but also more transient attitudes about policies or speciﬁc behaviors. “The
RSM views selective exposure to attitude-consistent content and media eﬀects as two components
of a larger dynamic process by which such social identities, attitudes, and behaviors are
maintained,” wrote Slater (2015, p. 371), noting further that “the process of media selection and
eﬀects of exposure to selected media is dynamic and ongoing” (p. 372).
The RSM originated in panel survey studies with adolescents and thus highlights the role of
selective media use for socialization of (identity-relevant) attitudes and later maintenance thereof.
Although data reviewed by Slater (2015) suggest connections in line with the RSM’s view of
a dynamic interplay of media choices and eﬀects, the predicted two-way eﬀects over time did not
always emerge, given that there is a certain stability in attitudes that make the demonstration of
inﬂuences challenging. Per its name, the RSM largely postulates the reinforcement of attitudes
through selective media use, once attitudes have formed in the socialization process. In this regard,
the model aligns with classic views that media are selectively attended such that existing attitudes
are generally reinforced (Klapper, 1960). The ﬁrst presentation of the model implied downward
spiraling reinforcement of negative eﬀects (i.e., teens with aggressive tendencies seek out violent
video games and become increasingly aggressive over time as a result). In a later iteration, Slater
(2015) highlighted that the suggested processes usually work toward a homeostasis.
Another recent model that highlights dynamic, two-way inﬂuences between selective media
use and eﬀects over time is Valkenburg and Peter’s (2013) diﬀerential susceptibility to media
eﬀects model (DSMM). It postulates that media eﬀects are contingent on dispositional, developmental,
and social conditions. The authors suggested that cognition, aﬀect, and excitation mediate
media eﬀects, similar to steps described in the DTA by Früh and Schönbach (1982). Overall,
strong parallels exist between DSMM and DTA, as Valkenburg and Peter (2013) write, “the differential-susceptibility
variables have two roles; they act as predictors of media use and as moderators
of the eﬀect of media use on media response states” (p. 231), and “media eﬀects are
transactional; they not only inﬂuence media use, but also the media response states, and diﬀerential-susceptibility
variables” (p. 235).
A review of these models suggests a consensus that numerous recipient characteristics and
contexts—cognitive, physiological, dispositional, developmental, and social aspects—inﬂuence
what media content is selected. Moreover, the outlined models in unison imply that media
exposure subsequently inﬂuences these characteristics, which brings about dynamic transactions
of media selection and eﬀects over time. The DTA, RSM, and DSMM are all characterized by
a rather generalized take on media exposure patterns and rely on panel designs and self-reports
for supporting evidence, from which user motivations were inferred. In contrast, the next perspective
has a much more situation-speciﬁc approach that uses observational measures and
(quasi-)experimental designs.
Selective Exposure Paradigm
Whereas the research traditions outlined above remained relatively broad, either with inventories
of possible media use motivations (for U&G) or generic predictions of reinforcement motivations
or vulnerability to media eﬀects (for dynamic-transactional models), the research
perspective described in the present section has yielded more speciﬁc postulations. Studies
rooted in the selective exposure paradigm built on psychological concepts and methods to
Media Choice and Selective Exposure • 151
conceptualize this problem. Zillmann and Bryant (1985) were front-runners in this development,
both with their own studies (e.g., Bryant & Zillmann, 1984) and in an edited volume on
selective exposure from 1985. Zillmann’s mood management theory (1988) was rooted in psychological
work on cognitive dissonance (see below) and arousal regulation, but became the
ﬁrst inﬂuential account of how individuals select media messages that provided speciﬁc, testable
hypotheses and that was situated in communication science. Additional theorizing to explain
and predict how media users choose messages have since emerged, whereas the advent of computerized
research methods and online media led selective exposure research to increasingly use
software to unobtrusively log speciﬁc media users’ choice behaviors and to enable sophisticated
(quasi-)experimental procedures (review by Knobloch-Westerwick, 2015a).
Although survey methods are still commonly used (e.g., Skovsgaard, Shehata, & Strömbäck,
2016) and provide helpful insights, methodological concerns regarding self-reports led scientists
to pursue a diﬀerent paradigm. In this vein, numerous researchers used observational measures of
media exposure (e.g., Kim, 2009; see review by Knobloch-Westerwick, 2015a), which is characteristic
of the selective exposure paradigm. This advancement is important in light of ample evidence
that individuals’ recollection of self-reported media use is scant and questionable (e.g., Jerit et al.,
2016; Prior, 2009). While scholars continue to debate how to best capture media use in surveys
(de Vreese & Neijens, 2016), validation studies ﬁnd that self-report measures of selective exposure
do not correlate with observational data, or do so only weakly (Tsfati, 2016). Sometimes media
use diaries, momentary assessments, or web browsing trackers serve to capture media use
(Scherer, Bickham, Shrier, & Rich, 2015). But a particularly fruitful line of research has relied on
tracking speciﬁc media exposure instances in relatively controlled contexts that feature messages
that represent content categories of theoretical relevance. For instance, studies by Kim (2009),
Iyengar and Hahn (2009), Graf and Aday (2008), Jang (2014) and Knobloch-Westerwick (2007)
all tracked what messages media users selectively attended to from arrays of messages that took
pro and con stances on political issues. This set only illustrates the numerous studies that have
used behavioral media exposure measures, which all relied on computerized methods. The basic
approach of providing research participants with an array of messages to then record their selections
goes back to much earlier work that allowed participants to pick out printed messages (e.g.,
Biswas, Riﬀe, & Zillmann, 1994; Freedman, 1965) or tracked TV remote control use (Bryant &
Zillmann, 1984). The theoretical accounts for what drives selective exposure compiled in the next
section were primarily derived from this approach.
Theoretical Accounts for Selective Media Exposure
Interests and Issue Publics
Obviously, individuals’ interests foster selective exposure to related messages (Bolsen & Leeper,
2013; Kim, 2009; Skovsgaard et al., 2016). The term issue publics is often used to describe the
phenomenon that sections of a larger audience hold interest in an issue and thus more often
choose related information and become more knowledgeable (e.g., Iyengar, 1990). However, the
notion of interest in itself does not clarify what factors instigate a motivation to seek out information
on a particular issue. Three aspects were suggested to explain from where interest stems
(Knobloch-Westerwick, 2014). First, self-interest can attract one to a topic. Naturally, students
are more interested in higher education issues, given that they may be aﬀected
themselves. Second, aﬃliation with particular groups—even without being a member of that
152 • Silvia Knobloch-Westerwick et al.
group—can induce interest. Third, values can instigate particular interests; for instance, a retiree
may not be remotely aﬀected by abortion laws but still follow the topic due to religious beliefs.
Cognitive Dissonance Theory
The phenomenon of political attitudes and partisanship shaping selective exposure to politically
aligned messages was ﬁrst discussed by Lazarsfeld and colleagues (1948), which inspired Festinger’s
(1957) theory of cognitive dissonance. Accordingly, individuals experience tension and discomfort
if they encounter information that challenges their preexisting views or behaviors. As a result, individuals
are thought to avoid such messages—a phenomenon commonly labeled conﬁrmation bias.
In the past 15 years, empirical research has frequently corroborated this predicted selection pattern
that information aligned with preexisting views or behaviors is preferred over challenging information
(Knobloch-Westerwick, 2015a). However, investigations in the past century yielded inconsistent
ﬁndings (Donsbach, 2009). Even though Festinger’s propositions were widely thought to be
plausible and restated in many textbooks, they were not always supported in early research. But
contemporary computerized methods of unobtrusively observing media choices have yielded
coherent support for Festinger’s predictions (Knobloch-Westerwick, 2015a). In addition to more
precise measurement, it is also possible that the context of online media, in which many of the
recent studies were conducted, is conducive to a stronger conﬁrmation bias than traditional media
contexts. Politically motivated selective exposure continues to inspire a ﬂourishing line of research.
Informational Utility (IU)
Aside from just preserving existing beliefs by preferring consistent messages, a motivation to
select information that helps to adapt to the environment has long been suggested. For instance,
an inﬂuential review by Sears and Freedman (1967) questioned whether dissonance avoidance
shapes information choices and proposed that informational utility (IU) may override this
avoidance. The concept of IU was further elaborated by Atkin (1973), but without empirical
evidence. A more detailed discussion of what IU means, along with empirical evidence in crosscultural
investigations, was provided by Knobloch-Westerwick and colleagues (summarized by
Knobloch-Westerwick, 2008; more recently, Johnson & Knobloch-Westerwick, 2017). Per this
model, the extent to which a message is perceived to have IU depends on four dimensions
(explained below), which are thought to contribute to this perception cumulatively. Importantly,
greater perceived IU is thought to predict greater selective exposure; for instance, related items
should be more likely to be chosen for consumption or attended to longer. Naturally, these
message characteristics can shape selective exposure best if they are signaled prominently
upfront (i.e., in the headline of a message).
First, the greater the magnitude of consequences described in the message, the greater the perceived
IU. For example, news about a comprehensive tax reform should be perceived as more useful
than news about small adjustments in tax law. Second, the likelihood of being aﬀected by the
reported event inﬂuences the perceived IU, with greater likelihood linked to greater IU. For the tax
news example, individuals below the tax liability income threshold will attach low or no IU to the
related news, as they are not directly aﬀected by the change in law. Third, immediacy—how soon or
distant in time the consequences of a reported event will materialize—shapes IU, such that reports
of events with soon-anticipated consequences will be perceived as more useful. Thus, hearing about
a tax reform that goes into eﬀect soon should be associated with greater IU. Fourth, eﬃcacy, the
Media Choice and Selective Exposure • 153
extent to which recipients perceive that they can inﬂuence consequences of a reported event, also
contributes to perceived IU, as greater potential for own impact makes the information more useful.
Hence, if the message induces a sense that recipients can take political action to inﬂuence the tax
reform or to adapt to upcoming tax requirements, the message will be perceived as more useful.
These predictions garnered support in several studies in the U.S. and Germany. Importantly, they
were found to apply to both positive and negative events. Thus, regardless of whether recipients
hope for tax beneﬁts or fear tax disadvantages, they should perceive IU per the outlined dimensions.
Mood Management Theory (MMT) and Mood Adjustment Approach
The next theoretical approach is not concerned with how media users might utilize messages
selectively to adjust to the environment and instead looks at how they might use them to regulate
inner states. Zillmann (1988) proposed that a key motivation driving media selection is the
optimization of moods. Mood management theory (MMT) does not focus on cognitions and
instead emphasizes mood states, as deﬁned by arousal levels and perceived valence of one’s own
mood state, as key concepts to predict what choices media users make. In a nutshell, it proposes
audience members select any kind of media message—music, movies, news, documentaries, etc.
—with the goal of enhancing their moods. More speciﬁcally, selective media use serves to regulate
arousal levels, such that users will select exciting messages to overcome states of boredom
and calming messages to overcome stress (Bryant & Zillmann, 1984). Also, media users seek
out messages that enhance the hedonic valence of mood. Moreover, if in a negative mood,
media users avoid messages that would remind them of the source of the negative mood. For
example, after failing an exam, a student might avoid a campus comedy, as it would remind her
of the setback. MMT was the ﬁrst theory with speciﬁc predictions on media choices that garnered
solid empirical support. Its predictions were found applicable for selective exposure to
TV, websites, news articles, and music, among others (Knobloch-Westerwick, 2006). Numerous
experimental, quasi-experimental, ﬁeld, and diary studies applied and corroborated its claims.
Nonetheless, MMT faced challenges. Its postulation that media users seek out messages that
enhance the valence of mood is challenged by the massive amounts of negative news and violent
entertainment, which appear well suited to ruin moods. How could the theory account for the
wide popularity of news about deplorable events, of music about heartbreak, and ﬁctional
accounts of violent conﬂict? This popularity can only be explained from an MMT perspective by
drawing on additional considerations. For example, negative events can increase excitation and in
turn lead to more intense enjoyment of a movie’s happy-ending. Furthermore, seeing others
suﬀer heartbreak or violence could instigate self-serving social comparisons that enhance moods
after all. In other words, observing others in deplorable life circumstances might make onlookers
feel better about themselves. For example, elderly TV viewers preferred watching a documentary
about a lonely old man, likely because they felt better oﬀ than the portrayed individual (Mares &
Cantor, 1992). Indeed, when applying MMT to social media posts, Johnson and KnoblochWesterwick
(2014) observed that people in negative moods viewed negatively valenced posts that
allowed for downward social comparison longer than positively valenced posts about others’ successes.
Hence, downward social comparisons—whether a media user might derive a sense of
superiority—can explain, based on MMT, why individuals select messages that portray others
negatively.
An additional challenge to MMT stemmed from observations that men and women did not
show consistent media choice patterns (e.g., Biswas et al., 1994). The notions that social
154 • Silvia Knobloch-Westerwick et al.
expectations and the drive to not just optimize moods but also adapt to anticipated requirements
instigated the mood adjustment approach (Knobloch, 2003; Knobloch-Westerwick, 2007).
Per this view, media users utilize media to shape their moods to match anticipated situations.
For example, Kevin might feel sluggish before his planned workout but could pick fast-paced
music to motivate himself for his run. In that case, the media message was not chosen based on
Kevin’s mood-improvement and maintenance goals (per MMT), but instead mood adjustment
to anticipated circumstances guided his selection. Coming back to gender diﬀerences, stereotyped
expectations for how individuals should act and feel diﬀer by gender: After a provocation,
a man might be expected to retaliate and stand his ground, whereas a woman might be
expected to withdraw—and media choices may help individuals to comply with such social
expectations. Indeed, this view of mood adjustment found empirical support (KnoblochWesterwick
& Alter, 2006), wherein men preferred negative content to sustain anger against
a provoker, whereas women preferred positive content to dissipate anger, but only for participants
who anticipated an opportunity to retaliate against the provoker. The trajectory of MMT
and mood adjustment evolved further based on such consideration of social contexts and situational
anticipations, combined with self-related aﬀect, as the next section shows.
Selective Exposure of Self- and Aﬀect-Management (SESAM) Model
The Selective Exposure Self- and Aﬀect-Management (SESAM) model (Knobloch-Westerwick,
2015b) proposes that people select messages to activate and regulate certain working self-concepts,
as well as aﬀective and cognitive states and their associated behaviors. The SESAM builds on the
dynamic self-concept (Markus & Wurf, 1987): People have dynamically changing, malleable selfconcepts,
which are shaped by both circumstances and choice. Working self-concepts are those
aspects of the self that are accessible in the moment. Going beyond the MMT and adjustment perspective,
the SESAM model suggests that people selectively attend to messages to activate particular
self-concepts (and not just aﬀective states) in their working self.
Thinking about oneself in a particular way, facilitated by selective media use, can be sought
out for many reasons, for example, because the particular self-facet induces pride or a sense of
belonging. Nicole may read Forbes Magazine because it activates her positive self-concept of an
accomplished entrepreneur. Becca, an Ohio State University alumnae, watches games played by
her alma mater’s football team—the “Buckeyes”—to activate her “Buckeye” self and feel connected
with the university community. Even if Nicole’s company is not doing well, and even if
Becca’s preferred team loses, they feel good about the related aspects of themselves and seek to
activate them in their working selves. Their selective exposure is then driven by self-consistency
motivations (which probably underlie most habitual media use) to uphold a sense of stability
and identity despite ﬂuid self-perceptions.
Per the SESAM, selective media use facilitates behavior regulation, when media users activate
a self-facet through media exposure to accomplish a goal related to external rewards. For
instance, Jerry may read Men’s Health to activate his sense of being athletic to get motivated to
work out. If Jerry feels he falls short in his level of physical ﬁtness, but activates his athletic self
nonetheless through media use, he encourages himself toward physical activity and better
health. The selective exposure is then driven by a self-improvement motivation, often addressed
by upward social comparisons with media portrayals who may be doing better in a relevant
dimension (i.e., greater physical ﬁtness). The SESAM model thus conceptualizes the possibility
that media use can facilitate change and is not only a tool for reinforcing the status quo.
Media Choice and Selective Exposure • 155
Additionally, the SESAM proposes that self-enhancement motivation can drive selective
exposure, when users seek out portrayals of others or outgroups that provide an opportunity
for downward comparisons. For instance, after receiving negative test feedback, social media
users prefer viewing posts depicting others’ failures (compared to users who received positive
feedback) (Johnson & Knobloch-Westerwick, 2014). Several studies yielded that groups
that are subject to negative stereotyping (e.g., ageism, racial bias) exhibited a preference for
negative portrayals of outgroups (young people, whites) and derived a self-esteem boost
from that selective exposure (Knobloch-Westerwick, 2015a; Knobloch-Westerwick & Hastall,
2010).
Importantly, ongoing aﬀective experience, which is part of the working self-concept and
often a result of self-discrepancies, may prompt each of these motivations of self-consistency,
self-improvement, and self-enhancement. When attainability of a desirable future self is perceived
to be high, self-improvement motivation is more likely (Knobloch-Westerwick &
Romero, 2011); if it is low, people may rather engage in self-enhancement without aspiring to
change. Self-discrepancies wherein the actual self diﬀers from an ideal self or from an ought self
(i.e., who others expect us to be) can trigger aﬀect, per the SESAM. Moreover, the most basic
social comparison motive Festinger (1954) proposed, namely self-evaluation, will also drive
selective exposure: To gain an understanding of one’s own standing or performance regarding
a particular self-aspect, people compare themselves with others, oftentimes with similar others,
and selective media exposure certainly provides ample opportunity for doing so. For example,
when teens want to get an idea of how popular they are, they might consider the number of
“friends” they have on a particular social media platform. This observation will likely trigger
some self-evaluation and an aﬀective response.
Self-regulation through selective media use can have lasting eﬀects, as prolonged selective exposure
research demonstrated (Knobloch-Westerwick, Robinson, Willis, & Luong, in press). As media
messages are selected, aspects of the self-concept are rendered more salient and become more
chronically accessible. The SESAM has been successfully applied in a variety of contexts: selective
viewing of political ads (Marquart, Matthes, & Rapp, 2016) and controversial political messages
(e.g., Dvir-Gvirsman, 2017; Knobloch-Westerwick & Meng, 2011), selective media use when anticipating
challenging tasks (e.g., Luong & Knobloch-Westerwick, 2017), selective exposure to race portrayals
(e.g., Knobloch-Westerwick, 2015b), music videos (Karsay & Matthes, in press), gendered
role-portrayals (Knobloch-Westerwick et al., in press), and health communication (e.g., KnoblochWesterwick,
Johnson, & Westerwick, 2013). The SESAM also has been used to interpret selective
media use regarding ideal-body internalization (Rousseau & Eggermont, 2018) and multi-tasking
(van der Schuur, Baumgartner, Sumter, & Valkenburg, 2018). The role of self-discrepancies, related
to aﬀect per SESAM, was corroborated by Johnson and Ranzini (2018). With regard to speciﬁc
mechanisms through which impacts of selective media exposure on recipients occur, the SESAM
emphasizes social comparisons. Further social factors on selective exposure will be discussed in the
next section.
Social Factors in Selective Exposure
While the SESAM considers social comparisons and anticipations, a wider array of research on
social factors’ impacts on selective exposure has been conducted. Yet no single organizing
theory of social inﬂuence on selective exposure exists. Researchers have suggested various distinct
social goals inﬂuencing media consumption, including aﬃliation, persuasion, impression
156 • Silvia Knobloch-Westerwick et al.
management, and distinctiveness (e.g., Berger & Heath, 2007; Leary & Kowalski, 1990).
Although similarity and self-consistency frequently play an important role for selective exposure,
sometimes media portrayals that are dissimilar to the self may be sought out for selfimprovement
or self-enhancement. We will discuss social impacts on selective exposure in more
detail in this section.
The overarching notion that media users will prefer messages they associate with anticipated
conversations and desirable shared knowledge per aﬃliation goals has received empirical support
(e.g., Chaﬀee & McLeod, 1973). For example, Smith, Fabrigar, Powell, and Estrada (2007)
found a distinct preference for attitude-consistent information when participants expected to
talk with others who agree with them about a controversial issue. In experiments looking at the
selection of less controversial information, people selected more information when anticipating
any social interaction (e.g., Atkin, 1972; Dillman-Carpentier, 2009). The new media environment
allows for mass-sharing without actual conversation via proﬁles, “liking,” and so on, providing
a new context in which to study aﬃliation goals. There is evidence that popularity cues
can drive entertainment and news media-consumption per a bandwagon eﬀect (e.g., Fu, 2012;
Salganik, Dodds, & Watts, 2006).
Importantly, the exact nature of the anticipated social interaction can shape selective
exposure in distinct ways. For instance, people intuitively understand that it is important to
express socially acceptable moods in interactions and that the quality of social interactions
depends on how well aﬀective states match. Media use can facilitate functioning accordingly:
Anticipating interaction with a stranger was shown to prompt news reading that reﬂected
attempts to neutralize the mood induced beforehand, because participants preferred news
stories with an emotional tone that contrasted their mood; the anticipated mood of the partner
in the upcoming interaction also mattered (Erber, Wegner, & Therriault, 1996). Other
examples of how an anticipated interaction may matter can be found in early challenges to
the conﬁrmation bias (Freedman, 1965). Anticipating a need to defend one’s views to others
increased attitude-discrepant information selection. Selective exposure shows diﬀerent patterns
depending on whether the individual anticipates communicating with like-minded or diﬀerent-minded
others, which suggests that intentions to persuade others may shape selective
exposure.
Possibly the most overarching social inﬂuence on selective exposure, evident in many studies,
is the importance of similarity between media user and featured characters or sources. Speciﬁcally,
news consumers prefer portrayals of same-ethnicity (Knobloch-Westerwick, Appiah, & Alter,
2008), same-gender, and same-age characters (Knobloch-Westerwick & Hastall, 2006). Overall, it
appears that audience members prefer sources and portrayals that signal similarity with themselves;
the increasing prevalence of user-generated content may strengthen this tendency.
However, people strike a balance between similarity and uniqueness (e.g., Chan, Berger, &
Van Boven, 2012). For example, overly popular news or entertainment may be disdained in
favor of moderately popular messages (e.g., Berger & Heath, 2007; Knobloch-Westerwick,
Sharma, Hansen, & Alter, 2005; Messing & Westwood, 2014), in line with theories on impression
management (Leary & Kowalski, 1990) and optimal distinctiveness (Brewer, 1991). Moreover,
media users may seek out portrayals dissimilar to themselves, for self-improvement or
self-enhancement, per the SESAM model.
This brief sketch has outlined the complex ways that various inﬂuences shape selective
exposure. Message characteristics, anticipations of social interactions and comparisons, currently
accessible self-categorizations and self-perceptions, and technological circumstances all aﬀect
Media Choice and Selective Exposure • 157
media choices. More research is needed to disentangle and theorize these processes, especially
as user-generated content further complicates them.
Conclusion and Future Directions
Over decades of research, communication science is becoming increasingly speciﬁc in conceptualizing
and predicting what drives selective exposure to mediated messages. Contemporary approaches
all view media eﬀects as contingent upon individuals’ message selections, because media use occurs
predominantly in a selective fashion in high-choice media environments. They further suggest that
media eﬀects evolve in dynamic, transactional ways, wherein the user brings motivations to the
media use situation and is in turn inﬂuenced by media. Diﬀerences exist in how speciﬁc postulations
are and whether overarching patterns or situational behaviors are emphasized in research,
along with diﬀerent research designs and methods. Factors known to shape selective exposure
include issue interests, conﬁrmation bias, mood management, informational utility, selective exposure,
self and aﬀect management via social comparisons, in addition to social factors. Due to space
restrictions, the scope and level of detail of this review necessarily has limitations; for instance,
approaches focusing on selective use of health messages were neglected.
Interesting new research goes beyond antecedents of selective exposure and has begun to
address how such exposure inﬂuences media users (Knobloch-Westerwick, 2015b). For example,
political attitude polarization due to a conﬁrmation bias garnered numerous studies; recent
investigations also show that selective exposure shapes public opinion perceptions, as well as
gender role and life role salience (Dvir-Gvirsman, Garrett, & Tsfati, 2018; Knobloch-Westerwick
et al., in press; Sude, Knobloch-Westerwick, Robinson, & Westerwick, in press).
The societal relevance of selective exposure is bound to remain crucial, which calls for more
research. After all, media eﬀects can only come about when media users choose to attend to
a message. With the increasing number of channels, outlets, and sources, audiences become more
segmented and fragmented, possibly also more disconnected. The increase in outlets does not
necessarily mean that the content becomes more diverse as well. Certainly, when only three commercial
TV channels were on air, and viewers often chose to simply attend to the least annoying
programming available, audiences were more likely to consume the exact same message simultaneously
with others and to encounter new and unexpected things that could broaden their horizon.
With hundreds of TV channels available now, viewers will less frequently feel that the public is
largely attending to the same content. Also, when algorithms customize and pre-select content for
individual users based on their prior usage and big data patterns, do media users have more or
fewer choices? Although they can choose what media options are presented to them, they may
encounter and know fewer choices that are truly diﬀerent from their habitual media diet.
More research inspiration stems from the rise of social media and user-generated content:
How do content generation and social and technological online cues aﬀect selective media use
and eﬀects? This rise could imply that users generally become more self-aware and selfcentered,
in which case the focus on the media user’s self (per SESAM) becomes even more
compelling. In media contexts that allow for self-expression through a plethora of aﬀordances
to post, share, comment, like, personalize, and customize, media users likely connect mediated
content to self-perceptions more often than in traditional settings (Johnson & Ranzini, 2018;
Kang & Sundar, 2016). Possibly, high-choice media, along with more self-expression aﬀordances,
drive people into self-focused niches of media use and content generation, undermining
social connectedness. We don’t know yet.
158 • Silvia Knobloch-Westerwick et al.
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