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Antecedents of News Avoidance: Competing Effects of Political Interest, News Overload, Trust in News Media, and “News Finds Me” Perception


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Recent changes in the media environment make it easier than ever for people to actively shape their news repertoires according to their habits, needs, and preferences. As convenient as these practices seem, they may favor the development of misperceptions such as “news finds me” perception (NFM) and make it easier for some people to disconnect from news and political content. Building on the conceptualization of news avoidance as a general disposition and its consequential behaviors, this study jointly examines key individual-level predispositions that may motivate intentional news avoidance. Based on a two-wave survey collected in the United States, our results largely corroborate previous work showing the association of political interest, news overload, and trust in professional news with news avoidance, and stress the importance of including the NFM in the theoretical and empirical modelling of news avoidance. Our analyses also suggest that the linkages between these individual-level antecedents and news avoidance are contingent upon the design and robustness of the empirical tests, with NFM yielding the most consistent association across models.
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Antecedents of News Avoidance: Competing Effects of
Political Interest, News Overload, Trust in News Media,
and News Finds MePerception
Manuel Goyanes
, Alberto Ard
Homero Gil de Z
Department of Communication, Carlos III University, Madrid, Spain;
Instituto Universitario de
Neurociencia, Universidad de La Laguna, La Laguna, Spain;
Democracy Research Unit, Universidad
de Salamanca, Salamanca, Spain;
Laboratorio de Investigaci
on sobre Medios y sus Efectos,
Universidad de La Laguna, La Laguna, Spain;
Media Effects Research Lab, Pennsylvania State
University, USA;
Facultad de Comunicaci
on y Letras, Universidad Diego Portales, Chile
Recent changes in the media environment make it easier than
ever for people to actively shape their news repertoires according
to their habits, needs, and preferences. As convenient as these
practices seem, they may favor the development of mispercep-
tions such as news finds meperception (NFM) and make it eas-
ier for some people to disconnect from news and political
content. Building on the conceptualization of news avoidance as
a general disposition and its consequential behaviors, this study
jointly examines key individual-level predispositions that may
motivate intentional news avoidance. Based on a two-wave sur-
vey collected in the United States, our results largely corroborate
previous work showing the association of political interest, news
overload, and trust in professional news with news avoidance,
and stress the importance of including the NFM in the theoretical
and empirical modelling of news avoidance. Our analyses also
suggest that the linkages between these individual-level antece-
dents and news avoidance are contingent upon the design and
robustness of the empirical tests, with NFM yielding the most
consistent association across models.
News avoidance; political
interest; news overload;
trust in news media; news
finds meperception;
new media
In the last decade, a growing body of research has drawn attention to the fact that an
(apparently) increasing share of the population avoids the news. Although the diverse
definitions and operationalizations of the concept make it difficult to reach clear con-
clusions about the magnitude of the phenomenon (Skovsgaard and Andersen 2020),
research across countries suggest that news avoidance is a widespread challenge. A
recent report by Reuters Institute identified news avoiders in 36 countries in Europe,
Asia Pacific, and the Americas and reported figures ranging from 6% of respondents in
CONTACT Alberto Ard
evol-Abreu Departamento de Psicolog
ıa Cognitiva, Social y
Organizacional, Universidad de La Laguna, C/Prof. Jos
e Luis Moreno Becerra, La Laguna, 38200, Spain.
ß2021 Informa UK Limited, trading as Taylor & Francis Group
Japan to 57% in Turkey and Greecealthough these numbers are underestimates
since the study excluded those who used news less than once a month, see
Kalogeropoulos 2017. In the United States, this same report estimated the percentage
of news avoiders to be around 38%. More recent observations from network analysis
of Russian social media Vkontakte found that less than 15% of its users follow at least
one page of the major Russian media sources or blogs,a finding that the author
associates with a high rate of news avoiders (Urman 2019, 5171).
From a deliberative democracy perspective (Fishkin 2016), recurrently avoiding the
news may be problematic. News media provide citizens with essential information to
understand important political issues at the local, national, and international levels
(Moy et al. 2004). Without an appropriate knowledge of their political environment, it
is unlikely that people engage in reasoned deliberations and reach some form of con-
sensus. A similar argument applies to a competitive model of democracy, in which
politically knowledgeable citizens choose between a range of alternatives in the polit-
ical marketplace, primarily responding to the actions of political elites by voting
ack 2005, 334; see also Sartori 1987). According to this latter model of democ-
racy as an institutional arrangement (Elliott 1994), elections give informed people the
opportunity to select the more qualified candidate or party and keep politicians
accountable. News avoiders may therefore miss the most critical link to politically
relevant information in the public sphere(Toff and Kalogeropoulos 2020, 367).
But why some people avoid news, whether occasionally or regularly? Several recent
studies in both communication and political sciencemostly based on cross-sectional
survey data
have examined potential individual (e.g., personal characteristics, emo-
tions, and thoughts) and contextual factors (e.g., democratic quality of the political and
media environment) that may account for the increasing levels of news avoidance (Park
2019; Song, Jung, and Kim 2017; Toff and Kalogeropoulos 2020). The former include
motivations such as 1) feelings of news overload, against which people would respond
with news avoidance as a remedial strategy (Lee, Kim, and Koh 2016;Park2019;Song,
Jung, and Kim 2017; see also Lee, Lindsey, and Kim 2017 for a negative result); 2) cogni-
tions such as media distrust or lack of confidence in the accuracy of the news
(Woodstock 2014, 843; see also Pentina and Tarafdar 2014; Serrano-Puche 2018;Toff
and Kalogeropoulos 2020); and 3) relatively stable personal dispositions such as political
interest (Str
ack, Djerf-Pierre, and Shehata 2013; see also Schiefele 1991).
Drawing on these previous findings, this study develops and tests an overarching
model that explores the competing explanatory power of different individual-level fac-
tors (i.e., cognitions and dispositions) that may be associated with intentional news
avoidance. Further, to account for the time-order of the proposed relationships and
provide a time-based benchmark against which to compare previous and subsequent
studies, we test our hypotheses with cross-sectional, lagged (4 months), and autore-
gressive panel models.
Typology and Measure of News Avoidance
Extant literature distinguishes between intentional and unintentional subtypes of news
avoidance, a division that focuses on motivational and behavioral aspects. Intentional
avoidance results from an individuals antipathy toward news, which motivates them
to actively opt-out of news exposure(Skovsgaard and Andersen 2020, 465)e.g.,
changing the T.V. channel when news comes on, unsubscribing from news content, or
unfollowing friends who post too much news (see Bode 2016; see also Skoric, Zhu,
and Lin 2018 for the related concept of selective avoidance). Differently, unintentional
news avoidance is not connected to dislike for news or to an active choice to limit
[] news consumption(Skovsgaard and Andersen 2020, 460). Unintentional news
avoiders prefer other media content, for example entertainment, and this preference
tends to displace news from their media diets,especially when it does not require
any effort to get entertainment content (Prior 2005; Skovsgaard and Andersen 2020).
All in all, news avoidance seems to be a phenomenon that covers different dimen-
sions and depends on individual motivations and structural conditions of media mar-
kets (Str
ack, Djerf-Pierre, and Shehata 2013). In this study, our approach to the
construct relates to its intentional type, as opposed to unintentional. Complementarily,
our operationalization of news avoidance relies on self-identification, which seems to
fit better with research questions on why people sometimes choose to turn their
backs to the news(Skovsgaard and Andersen 2020, 462).
Political Interest and News Avoidance
Although political interest has been described as the most powerful predictor of pol-
itical behaviors that make democracy work,the reasons why it develops (or not)
have not been fully explained (Prior 2010, 747). Political interest is a stable personal
disposition and an intrinsic motivation that energizes politically related behaviors
(Prior 2010) such as following news (Lecheler and de Vreese 2017; Str
ack and
Shehata 2010), engaging in political discussion (Shah et al. 2007), or participating in
politics (Blais and St-Vincent 2011).
Some of these positive outcomes of political interest seem to be even more pro-
nounced as media environments provide more choice opportunities (i.e., more media
channels, more diverse content, and greater ease for managing ones news repertoires)
(see Prior 2005). In media-saturated environments, those who are not interested in
politics can reduce their exposure to news in favor of other contents and genres they
like or prefer (e.g., entertainment, see Str
ack, Djerf-Pierre, and Shehata 2013).
Although increased choice opportunities are crucial for explaining the displacement
effects of entertainment on news content (passive avoidance), they also make it easier
for the politically uninterested to intentionally switch to another channel when TV
news starts, customize their social media feed to not include news, or mute instant
messaging groups that become too political.Exactly the opposite is true for those
highly interested in politics: Media-rich environments and online/mobile technologies
give them the possibility to actively broaden their news intake as much as they want.
Supporting these theoretical claims, a survey-based longitudinal study conducted
over 1986 and 2010 in Sweden found that, over timeas media choices increased,
the positive effect of political interest on news media use (including print and online
newspapers, TV news, and public service radio; and with the sole exception of tabloid
newspapers) increased (Str
ack, Djerf-Pierre, and Shehata 2013). Prior (2005), using
nationally representative data from the United States, observed that only in a high
media choice environment (i.e., access to cable TV and internet) respondentspreferen-
ces (for entertainment over news) predicted their levels of political knowledge. Based
on the foregoing discussion, we predict that the politically uninterested will be more
likely to intentionally avoid news:
H1: Political interest is negatively associated with news avoidance a) in cross-sectional, b)
time-lagged, and c) autoregressive models.
News Overload and News Avoidance as a Remedial Strategy
In addition to increases in media choice, modern communication technologies have
vastly expanded the amount of available news and the frequency with which (at least
some) people use it. For some scholars, news media and news itself have become
ambient like the air we breathe(Hargreaves and Thomas, cited by Hermida 2010).
The widespread adoption of home and mobile broadband allows people to access
news anytime, anywhere(Schrøder 2015, 15) and, we may add, from any media
source and in any desired amount. Furthermore, current patterns of news consump-
tion include not only intentional but also unintentional exposure: People may encoun-
ter news while doing other online activities such as booking an airline ticket or using
social media to connect with friends (Boczkowski, Mitchelstein, and Matassi 2018;
Goyanes and Demeter 2020). Even though unintentional exposure to news may elicit
beneficial effects on political knowledge (Lee and Kim 2017) and participation ( Kim et
al. 2013), people may stumble upon news at inopportune moments. Thus, they may
encounter news in working hours or when they have gone online with different pur-
poses (for example, for social interaction, see Holton and Chyi 2012).
As a specific instance of the broader phenomenon of information overload (Song,
Jung, and Kim 2017), feelings of news overload emerge when an individual faces an
oversupply of news that interferes with their ability to adequately process it (Lee,
Lindsey, and Kim 2017). People may perceive news overload because they feel there
are more relevant news out there than they can process or because news get in their
waywhen they do not want to encounter it (see Holton and Chyi 2012; Lee, Kim, and
Koh 2016). News overload can create stress and negatively affect both psychological
and physiological health(Lee, Kim, and Koh 2016, 2; see also Misra and Stokols 2012),
and people may therefore search for coping strategies. One of them is to actively
avoid news, either completely or partially (Pentina and Tarafdar 2014). Extant empirical
research, however, provide mixed support for this assumption. In a cross-sectional
design using survey data from South Korean internet users, Song, Jung, and Kim
(2017) observed that news overload relates to news fatigue, which is in turn positively
associated with news avoidance. In the words of the authors, if the amount of news
requiring processing is large enough, people feel fatigued [and] avoid news to get rid
of the cognitive burden(1184). Another study also using survey data from South
Korean online panelists found that perceived news overload in social media has direct
and indirect (through reduced news efficacy) relationships with news avoidance (Park
2019). In contrast, Lee, Lindsey, and Kim (2017) did not find any significant association
between perceived news information overload and news avoidance in their sample of
American citizens (258, Table 1). In line with this, we ask the following
research question:
RQ1: What is the relationship between news overload and news avoidance (a) in cross-
sectional, (b) time-lagged, and (c) autoregressive models?
(Dis)Trust in Professional News and News Avoidance
A third reason why people may avoid news is that they do not trust the media and
the news content they provide, even when it is fact-checked (see Ard
Delponti, and Rodr
uemert 2020). In a recent survey conducted in four
countries (United States, United Kingdom, Denmark, and Spain), Reuters Institute asked
475 news avoiders about their reasons for not exposing themselves to news on a
regular basis(Schrøder 2016). While most news avoiders alluded to their general lack
of political interest, time, or higher preference for entertainment, other respondents
suggested they did not trust the media. Thus, one of these news avoiders verbalized:
The BBC are a propaganda machine they do not give the news as it is, they just give
their view of the news and cant be trusted(Schrøder 2016).
Similarly, a secondary analysis of Reuters data focusing on the Spanish subsample
of news avoiders found that almost one in three of them (29%) reported that they
could not rely on news to be true(Serrano-Puche 2018, 314). One Spanish respond-
ent added this way: We are told just what the rulers want us to know Its all a lie
(314). The 2017 Digital News Report further explored this issue by including a single
question about the frequency with which respondents found themselves actively try-
ing to avoid the news these days(Toff and Kalogeropoulos 2020, 373). A multilevel
analysis of this cross-sectional dataset (67,245 respondents across 35 countries) found
that trust in the news was one of the strongest individual-level predictors of news
avoidance (Toff and Kalogeropoulos 2020).
Some similar interpretation can be found in Woodstocks(2014) qualitative
approach to news resisters.Woodstocks informants shared a distrust of corporate
influence and a lack of confidence in the accuracy of the newsand criticized news
media for over-relying on official governmental sourcesand spreading incorrect and
misinformed reportage(843, 844). Some participants experienced news avoidance as
a conscious strategy to prevent their media distrust from spreading to more general
perceptions of the public good (840). Accordingly, we state our second hypothesis:
H2: Trust in professional news is negatively associated with news avoidance a) in cross-
sectional, b) time-lagged, and c) autoregressive models.
Avoiding News Because It Will Find Them Anyway
Increased opportunities for unintentional exposure to news in technologically intensive
environments can lead some people to develop misperceptions about the ways they
can gain political knowledge. An example of this is what has come to be known as
the news finds me perception (NFM), defined as the belief that one can be well
informed without having to actively seek for and follow newsbecause one can get
the news indirectly, via their general Internet use, peers, and connections within
online social networks”—(Gil de Z
niga, Weeks, and Ard
evol-Abreu 2017, 112). This
mistaken belief seems to have behavioral and cognitive implications that may be
problematic for the development of a healthier and more informed democracy. Thus,
the NFM has been found to be associated with lower levels of traditional news media
use (TV and newspapers) and higher exposure to news through social media (Gil de
niga, Weeks, and Ard
evol-Abreu 2017). Regretfully, this increased exposure to social
media news does not translate into political knowledge. In fact, those with higher
NFM tend to be less politically knowledgeable, both in a cross-sectional and a longitu-
dinal analysis (Gil de Z
niga, Weeks, and Ard
evol-Abreu 2017; Lee 2020).
Another recent account suggests that the NFM is a three-dimensional construct that
encompasses epistemic, motivational, and instrumental elements (i.e., a being
informed,anot seeking,and a reliance on peerscomponent, respectively; Song, Gil
de Z
niga, and Boomgaarden 2020, 48). The authors, however, consider the not
seekingdimension of NFM as a “‘passivemotivation of consuming news contents, or
lack thereof(49, 50), a description that seems to overlap with the unintentional type of
news avoidance. Conceivably, this is the case because the more intentional news avoid-
ance mechanism emerges as a consequence of the NFM (i.e., a long-term effect). The lat-
ter is the theoretical approach pursued in this study. In other words, even though those
who score high on NFM may not initially make efforts to search for and follow news,
their misperception may, over time, drive intentional avoidance behaviors.
From a theoretical perspective, individuals who are high in NFM may have unpleas-
ant experiences with the news that progressively transform its presence into a nega-
tive incentive. As such, news could create in the person an expectation that [ ]
unattractive consequences are forthcoming(Reeve 2009, 114) and therefore energize
avoidance behaviors. Because individuals who hold the NFM are less exposed to trad-
itional news sources and are less politically knowledgeable, one can assume that it
will become increasingly harder for them to fully grasp the news content, even if they
try to do so. They are, so to speak, out of practice, and lack domain-specific know-
ledge that is required for deciphering the news story. They are mostly used to glance
over decontextualized headlines and their accompanying pictures on social media and
then move on to the next post. Reading the whole news content or watching news
programs may therefore become a frustrating or at least unsatisfactory experience
that translates to self-doubt about ones capacity to cope with the news environment
(i.e., reduced self-efficacy).
Under this framework, it is easy to explain why increased social media use for news
among those who believe that news will find them does not predict political know-
ledge (see indirect pathway in Gil de Z
niga, Weeks, and Ard
evol-Abreu 2017; see also
the direct and indirect relationships, through NFM, between social media news use
and political knowledge in Lee 2020). Unintentional exposure to news on social media
and intentional news avoidance may take place consecutively, one after the other.
Even after stumbling upona piece of news, individuals high in NFM may shift their
gaze toward a different post on the page or scroll down in search of a non-news
related post as a news avoidance behavior. In this case, mere exposure to news would
not translate into political knowledge. Hence, we present our final hypothesis:
H3: NFM is positively associated with news avoidance a) in cross-sectional, b) time-lagged,
and c) autoregressive models.
To examine the hypothesized relationships, we used data from a larger project on
emerging patterns of media use and their relationship with peoples attitudes, beliefs,
and behaviors. As part of this project, we administered three waves of online surveys
in the United States between June 2019 and February 2020. The questionnaires were
designed and distributed using Qualtrics web-based software. To recruit a diverse sam-
ple of respondents, we enlisted the services of the international polling organization
Ipsos in Austria. Ipsos distributed the survey link to 3,000 of their panel members,
seeking to mirror the United States census in terms of demographic variables (i.e., age,
gender, and education, see Gil de Z
niga et al. 2021). For this study, we used data
from the first and the second wave
, delivered four months apart (June and October
2019, respectively). The final sample left 1,338 valid cases in the first wave (W
). In the
second wave (W
), Ipsos contacted these same respondents and obtained 511
valid responses.
Variables of Interest
News Finds MePerception
Following extant research (Song, Gil de Z
niga, and Boomgaarden 2020), we used the
following six-item measure of NFM: I rely on my friends to tell me whatsimportant
when news happens,”“I can be well-informed even when I dontactivelyfollowthe
news,”“I rely on information from my friends based on what they like or follow through
social media,”“I am up-to-date and informed about public affairs news, even when I do
not actively seek news myself,”“I do not worry about keeping up with the news
because I know news will find me,”“I do not have to actively seek news because when
important public affairs break, they will get to me via social media(averaged scale,
1¼strongly disagree to 10 ¼strongly agree;W
Cronbachsa¼.82; M¼4.68; SD ¼1.95).
Trust in Professional News
This two-item construct probes respondents trust (from 1 ¼not at all to
10 ¼completely) in news that comes from mainstream news media (e.g., newspapers,
TV newscast, online news sites)and that is fact-checked(see Watson, Peng, and
Lewis 2019, for a similar measure). W
Spearman-Brown q¼.68; M¼6.24; SD ¼2.26).
News Overload
We drew on and adapted Jensen et al. (2014) cancer information overload scale,
replacing the wording cancerand cancer informationwith news,”“news sources,
etc. Our measurement instrument includes the following three assessments: There are
so many different news channels or sources, its hard to know which ones to follow,
There is not enough time to do all of the things recommended to stay-up-to-date on
news,and I feel overloaded by the amount of news/information I am supposed to
know(110 scale). W
Cronbachsa¼.80; M¼5.92; SD ¼2.14).
Political Interest
We asked participants about their degree of interest (1 ¼not at all to 10 ¼a great
deal)in information about whats going on in politics and public affairsand about
their level of attention (1 ¼not at all to 10 ¼very closely)to information about whats
going on in politics and public affairs(see a similar operationalization in Lee and Kim
2017). Two-item scale; W
Spearman-Brown q¼.94; M¼6.13; SD ¼2.72).
Intentional News Avoidance
Our main dependent variable captures participantsdislike for news, which motivates
them to actively opt-out of news exposure(Skovsgaard and Andersen 2020,465).We
asked respondents to self-identify as news avoiders (see Skovsgaard and Andersen 2020;
Van den Bulck 2006) by indicating their level of agreement (110 scale) with the follow-
ing three items: When I come across news, I move on to read/watch/listen to some-
thing else,”“Usually the news is not interesting enough to read/watch/listen,and If
the news annoys or bother me, I immediately move on to do something else(W
Cronbachsa¼.80; M¼5.06; SD ¼2.21; W
Cronbachsa¼.82; M¼4.98; SD ¼2.31).
Control Variables
Some of our regression models included three or four blocks of control variables that
may impact respondentslevel of news avoidance (see Lee, Kim, and Koh 2016; Park
2019; Serrano-Puche 2018;Str
ack, Djerf-Pierre, and Shehata 2013;Toffand
Kalogeropoulos 2020): political antecedents, news media uses, demographics and, in
autoregressive models, the W
measure of the dependent variable. To measure strength of
partisanship, we asked respondents whether they usually think of themselves as
Republicans, Democrats, or Independents (from 0 ¼strong Democrat,through
5¼Independent to 10 ¼strong Republican). We then folded the scale so that low values
indicate weak- and high values strong-partisanship, irrespective of party (see a similar
strategy in Greene 2004). Internal political efficacy was measured with the averaged value
of the responses to the following items: I have a good understanding of the important
political issues facing our country,and I consider myself well qualified to participate in
politics.The block of news media uses included newspapers news (three item-measure
inquiring about respondentsfrequency of use of national newspapers,”“local news-
papers,or printed), radio news (two items about the frequency with which they get
news from radio newssuch as NPR or talk shows, and from radiomore generally), TV
news (six-item scale measuring how often respondents get news from network TV news,
local television news,”“MSNBC cable news,”“CNN cable news,”“FOX cable news,and
televisionmore generally), online news (three items asking respondents how often they
get news from online news sites,”“citizen journalism sites,and local news online sites),
and social media news (thirteen items about the use of different social media platforms
for news, including Facebook, Twitter, Instagram, Snapchat, etc.). Finally, we also con-
trolled for a set of demographic variables, measured with single items: age group (W
median ¼3[3655 years old]), gender (W
, 53.2% females), education (W
median ¼3
[some college]), family household income (W
median ¼4 [$50,00099,999]) and race or
ethnicity (W
, 75.2% White or Caucasian).
Statistical Analyses
We run a series of cross-sectional, lagged, and autoregressive ordinary least square
(OLS) regression models. In the cross-sectional models, both the predictors and the
dependent variable are measured in W
. The lagged models include predictors in W
and the dependent variable in W
. Finally, the autoregressive models are similar to the
lagged ones, but they include as another predictor the W
measure of the dependent
variable. While this latter approach does not establish causality, it adds the time
sequence of causes and effect. To test our hypotheses, we first conducted relatively
uncontrolled regression models that included all the independent variables of interest.
We then incorporated several controls to account for other variables that may affect
news avoidance, as explained above. To estimate our multivariate regression models,
we used SPSS version 25. Significance tests for regression coefficients are based on
the Huber-White robust method and were computed using the HCREG macro for SPSS
(HC0, see Hayes and Cai 2007).
To test whether our scales of news finds me perception, news overload, and news avoid-
ance assess distinctbut correlatedconstructs, we first performed a principal axis
factoring with Oblimin rotation. This analysis produced three factors that explained
63% of the total variance and fit our three constructs (Table 1). H1 stated a negative
association between political interest and news avoidance. The present analyses pro-
vide only partial support for this prediction across regression models. Results in Figure
1show that political interest is negatively associated with news avoidance in the
cross-sectional (H1a, b¼.142, p<.001) and lagged models (H1b, b¼.116,
p¼.010), but not in the autoregressive test (H1c). When we consider other variables
Table 1. Principal axis factoring of news finds me, news overload, and news avoidance.
Item News Finds Me News Overload News Avoidance
I rely on my friends to tell me whats[].587 .008 .090
I can be well informed [ ].685 .016 .021
I rely on information from my friends [ ].657 .084 .100
Iamupto date and informed [ ].651 .053 .131
I do not worry about keeping up with [ ].617 .031 .094
I do not have to actively seek news [ ].683 .036 .023
There are so many different news channels [ ] .049 .611 .072
There is not enough time to do all of the things .038 .870 .043
I feel overloaded by the amount of news [ ] .034 .751 .040
When I come across news, I move on [ ] .066 .059 2.740
Usually the news is not interesting enough [ ] .051 .086 2.880
If the news annoys or bother me [ ].028 .137 2.566
Notes: Values are pattern loadings from the pattern matrix after direct oblimin rotation (W
measures, minimum
eigenvalue of 1.0). Primary loadings of a variable on a factor are indicated by boldface type. Kaier-Meier-Olkin meas-
ure of sampling adequacy ¼.845; Bartletts test of sphericity, v2 (66) ¼5868.18, p<.001.
that may explain news avoidance (Table 2), the beta coefficient of political interest
yields statistical significance only in the cross-sectional analysis (H1a, b¼.155,
p<.001), but not in the lagged or the autoregressive tests.
The first research question asked about the possible relationship between news
overload and news avoidance. As shown in Figure 1, more parsimonious regression
models provide only partial empirical support for this association: news overload is
associated with news avoidance in the cross-sectional (RQ1a, b¼.333, p<.001) and
lagged tests (RQ1b, b¼.191, p<.001), but not when we include the W
measure of
news avoidance in the analysis (RQ1c). These findings are mirrored in the more strin-
gent models in Table 2: the beta value for news overload is significant in the cross-
sectional (RQ1a, b¼.340, p<.001) and lagged studies (RQ1b, b¼.202, p<.001), but
not in the autoregressive model (RQ1c).
H2 posited that trust in professional news would be negatively associated with
news avoidance. Analyses provide support for H2a and H2b, but not for H2c. As
shown in Figure 1, this association is negative and significant in the analysis of W
cross-sectional data (H2a, b¼.117, p<.001) and in the W
lagged analysis (H2b,
b¼.121, p¼.006). But, again, once we include the W
measure of the dependent
variable as a control in the regression, the relationship becomes nonsignificant (H2c).
We obtained essentially the same results if we account for all other variables in blocks
1to4(Table 2). Trust in professional news is negatively associated with news avoid-
ance cross-sectionally (H2a, b¼.152, p<.001) and in the lagged model (H2b,
b¼.102, p¼.047), but the relationship becomes less stark as the beta coefficient
does not reach statistical significance in the autoregressive test (H2c).
Figure 1 .Regression models of political interest, news overload, trust in professional news, and
news finds meperception on news avoidance.
Note: Sample sizes: Cross-sectional model n¼1,206. Lagged n¼451. Autoregressive n¼449. W
¼Wave 1, W
Wave 2. Continuous path entries are standardized regression coefficients for OLS regression at p<.05 or better.
Significance tests are computed using the Huber-White robust method (HC0, see Hayes and Cai 2007).
Finally, we also predicted a positive association between NFM and news avoidance
(H3). Results in Figure 1 and Table 2 provide support for H3a and H3b. In the more
frugal models, NFM is associated with news avoidance cross-sectionally (H3a, b¼.379,
p<.001) and in the lagged (H3b, b¼.376, p<.001) and autoregressive tests (H3c,
b¼.189, p<.001). In the more stringent models in Table 2, NFM is also negatively
correlated with news avoidance in the cross-sectional (b¼.283, p<.001) and lagged
tests (b¼.287, p<.001), being this association marginally significant in the autoregres-
sive analysis (b¼.111, p¼.071).
The present study explored key individual-level antecedents that may account for peo-
ples intentional news avoidance behavior. Our analyses present insightful evidence
that moves forward the literature on intentional news avoidance.
At the methodological level, we report several regression-based models that allow
for the easy comparability of different study designs: cross-sectional, lagged, or autore-
gressive, on the one hand; and more parsimonious or more stringent on the other.
Table 2. Controlled regression models predicting news avoidance.
News avoidance
Predictors Cross-Sectional Lagged Autoregressive
(Wave 1) (Wave 2) (Wave 2)
Block 1: Autoregressive W
News avoidance ––.530
Block 2: Demographics W
Age group .045 .009 .024
Gender (1 ¼female) .035 .058 .031
Race (1 ¼White or Caucasian) .012 .094
Income .014 .007 .031
Education .022 .013 .007
5.3% 6.4% 1.4%
Block 3: Political antecedents W
Strength of partisanship .045 .025 .023
Internal political efficacy .017 .001 .023
1.3% 2.1% 0.3%
Block 4: News media uses W
Newspapers news .032 .002 .034
Radio news .039 .019 .039
TV news .030 .109.122
Online news .037 .008 .025
Social media news .121 .110 .051
8.1% 6.1% 1.4%
Block 5: Variables of interest W
Political interest .155 .105 .013
News overload .340 .202 .022
Trust in professional news .152 .102.020
News finds me perception .283 .287 .110
21.5% 12.6% 0.8%
Total R
36.2% 27.2% 43.6%
Note. Sample sizes: Cross sectional model n¼1,063. Lagged n¼408. Autoregressive n¼406. W
¼Wave 1, W
Wave 2. Standardized regression coefficients reported. Significance tests are computed using the Huber-White robust
method (HC0, see Hayes and Cai 2007).
#p<.10; p<.05; p<.01; p<.001 (two-tailed).
These detailed analyses replicate and provide a degree of comparability with previous
studies that have mostly employed cross-sectional designs and a variable number of
controls. They also establish comparative benchmarks for future longitudinal designs
that may use different time frames between waves (e.g., less than for months).
Furthermore, our different models illustrate the gradual reduction of the effect size
when the autoregressive control (W
measure of the dependent variable) and the
three blocks of demographics, political antecedents, and news media uses are
accounted for. Accordingly, our results provide a comprehensive picture of key individ-
ual level-antecedents of news avoidance, suggesting that their role as significant pre-
dictors is contingent upon both the study design and the competing power of diverse
variables of interest.
We hypothesized that political interest is negatively related to news avoidance. This
is in line with Str
ack and colleagues(2013) longitudinal study in Sweden, where
political interest became a stronger predictor of traditional news media use over time,
as the environment offered more media choices. The hypothesis also aligns with the
cross-sectional and multi-level study by Toff and Kalogeropoulos (2020), which used
ReutersDigital News Report data. Consistent with these previous findings, we found
political interest to be a negative predictor of news overload in both cross-sectional
models. However, once we consider the time order of the assumed causality
), the association only remains statistically significant in the first lagged
regression (the more frugal one), but not in the second lagged model (with the full
set of controls) or in the autoregressive tests. Thus, political interest proved to be the
weakest predictor among our interest variables. In our view, this does not mean that
political interest has nothing to do with news avoidance. However, our results are sug-
gestive that political interest shares an important part of its variance with the other
variables of interest (i.e., news overload, trust in professional news, and NFM), and its
unique contribution to news avoidance may wane once one considers other important
individual-level predictors. Further studies should manipulate situationalpolitical
interest (see Prior and Bougher 2018) in an experimental context and further elucidate
its causal role in (and unique contribution to) news avoidance.
News overload showed a statistically significant association with news avoidance in
both cross-sectional regressions and in both lagged models. This is in line with Song
and colleagues (2017) findings based on cross-sectional data, and with those of Parks
(2019) two-wave study in South Korea. News avoidance may therefore be understood
as a coping strategy for perceived news overload, an attempt to free cognitive resour-
ces in a saturated news media environmentor perceived as such. As effective as
news avoidance may be for reducing cognitive load, it may also have undesirable con-
sequences for democracies, whether one understands democracy as a deliberative pro-
cess or more narrowly as a competition for political power (Fishkin 2016; Str
2005). The time sequence of the hypothesized influence of news overload on news
avoidance could however not be established in our sample, because once we
accounted for the baseline level of news avoidance in the autoregressive model, the
correlation vanished. Further longitudinal studies could explore whether the strength
of this association is sensitive to changes in the time lag between waves, and also try
to isolate the unique influence of news overload through an experimental design.
Our findings about the role of trust in professional news in predicting news avoid-
ance parallel those of news overloadalthough the sign of the association is negative
in this case: The more one trusts professional news, the less one avoids the news.
Trust in professional news reduces news avoidance in all our cross-sectional and
lagged analyses, which mirrors Toff and Kalogeropoulos (2020) findings based on
cross-sectional, multilevel data analysis, as well as additional qualitative observations
provided by Woodstock (2014). These findings also align with previous empirical
assessments about the positive relationship between media trust and media use
(although the literature suggest that the strength of this association is rather small
and, sometimes, null, see Ard
evol-Abreu and Gil de Z
niga 2017; Tsfati 2010; Tsfati
and Cappella 2003). However, once our modeling strategy considers both the time lag
and the baseline measure of news avoidance with autoregressive models, we cannot
reject the null hypothesis that there is no association between trust in professional
news and news avoidance. This does not necessarily mean that trust in professional
news does not play a role in explaining news avoidance, but this potential effect
should be reevaluated in the light of the competing influences of other individual-
level factors, notably the NFM.
According to our longitudinal data, the most promising individual-level antecedent
of news avoidance, besides TV news use, is the NFM. In our sample, those who believe
that they do not need to actively follow the news to be well-informed since the news
will find them, are more likely to become news avoiders in five out of our six models:
in both cross-sectional models, in both lagged regressions, and in the first autoregres-
sive test (the more frugal one). The association NFM-news avoidance is only marginally
present (p¼.07) in the most stringent autoregressive analysis. But even in this latter
model, NFM has the second largest beta coefficient among the 16 predictors, lagging
only behind TV news use. Further studies should try to replicate this finding in other
samples, countries, and media environments.
While the NFM has been absent from the literature on news avoidance to date, our
findings indicate that this may be a pertinent individual-level construct to consider. As
we explained in the literature review section, we are not suggesting that intentional
news avoidance is part (i.e., a dimension) of NFM. NFM people may be motivated to
be informed, but they perceive the process of information acquisition to be different.
Our interpretation is that the passivemotivation to follow news (or lack thereof) that
characterizes those who perceive that news will find them may cultivate
an active
motivation (and associated behaviors) to avoid news. This double mechanism may
speak to the question of why increased exposure to social media news among those
who hold the NFM does not facilitate political learning (Gil de Z
niga and Diehl 2019;
Gil de Z
niga, Weeks, and Ard
evol-Abreu 2017, 119; Lee 2020). Thus, even when news
actually finds them on social media, they tend to escape it and move on to read/
watch/listen to something else(i.e., they avoid it, a behavior that does not enhance
political learning). Similarly, they may not invest the necessary cognitive efforts to pro-
cess the news content that finds them.
Complementarily, and different from NFM people, news avoiders are not always
unaware that they may be missing public interest information. For example, some of
Toff and Palmers, (2019) news avoiders felt that those who follow the news are
probably more in-tune with current affairs than [they are],while others referred to
political matters as stuff that [they]ve never really heard of(8). Some news avoiders
may therefore hold NFM while others do not, and they may limit their news consump-
tion for a variety of reasons: Because it negatively affects their mood (Kalogeropoulos
2017), or they are not confident about their ability to find and interpret news (Edgerly
2021), etc.
It is important to emphasize that this study is not without limitations, and our find-
ings should be interpreted with caution when making causality assumptions.
Observational studies such as the present one provide significantly limited opportuni-
ties for causal inference relative to rigorous experimental studies with random assign-
ment to condition(Newsom 2012, 171). From our data, we cannot rule out the
possibility that the association between our predictors and our dependent variable in
the cross-sectional analyses is due to the presence of uncontrolled variables, signaling
some degree of spuriousness, or that the direction of the effect is different for some
of the independent variables. Complementarily, the fact that our fully controlled longi-
tudinal analyses only found marginal evidence for a positive association between NFM
and news avoidance does not mean that all the other predictors do not play a role in
explaining avoidance. In the words of Eveland and Morey (2011), the timing of
wavesboth the timing of the initial wave, and also the lag between wavescould
lead to entirely different conclusions about the operation of the exact same theoretical
process(24). Perhaps a four-months lag is adequate to observe long time influences
of NFM, but too much to detect, for example, more immediate effects of news over-
load. In the latter case, the outcome variable may have decayed over time or been
affected by subsequent perceptions or environmental conditions. With these findings
in mind, future studies may test alternative time delays, more precisely adjusted to
each theoretical process.
A related limitation concerns the non-exhaustiveness of our regression models.
Although we tried to incorporate the main individual-level determinants of news
avoidance, we concur with one of the anonymous reviewers of this article that our set
of predictors do not cover all antecedents discussed in the literature. Thus, an inter-
view-based study in the United Kingdom explored the how and why behind the gen-
der gap in news consumptionand found structural inequalities, beliefs, and
perceptions that may explain news avoidance, especially among women (Toff and
Palmer 2019, 1563). These include participantsperception that news is for men; their
reliance on others to synthetize the news, and thus freeing up their time to manage
domestic activities; or their need to keep a positive emotional climate. Closely related
to the latter aspect, several qualitative studies suggest that some people avoid news
because of its negative tone: []Its very depressing, upsetting, frustrating, and
scary(Schrøder 2016; see also Kalogeropoulos 2017). We believe this limitation is
however attenuated by our inclusion of several demographic, perceptual, and belief
variables as controls in the models. Thus, genderwhich turned out not to be a sig-
nificant predictor, internal political efficacy, and strength of partisanship may serve
as partial proxies for some of Toff and Palmers underlying causes of news avoidance.
Finally, a caveat regarding the second item in our measure of trust in the news is
that there is not a complete equivalence between professional news and news that is
fact-checked”—because not all professional media outlets fact-check all the
information they publish. However, we see fact-checking as a hallmark of professional
news content on social media and as one of the tenets of good journalism(see
evol-Abreu, Delponti, and Rodr
uemert 2020; Bradshaw et al. 2020, and
the code of principles of the International Fact-Checking Network in Poynter Institute,
n. d.). Given the increasing proportion of Americans that get their news online and on
social media, we think that the item captures important nuances of the construct.
All in all, our findings largely corroborate previous work showing the association of
political interest, news overload, and trust in professional news with news avoidance;
and stress the importance of including the NFM in the theoretical and empirical mod-
elling of news avoidance. In light of the seemingly widespread proliferation of NFM
(Gil de Z
niga, Strauss, and Huber 2020), these findings are not good news for any
conception of democracy. People who do not actively seek news and take actions to
avoid unintentional exposure will hardly be able to learn about or discuss complex
political issues, engage in collective action for social change, or keep political elites
1. Park (2019) is an exception to this and uses two waves of survey data from South Korean
adults to test a model for direct and indirect effects of news overload on news avoidance.
Although not specifically focused on news avoidance but rather on news consumption, it is
also relevant to mention the longitudinal study by Str
ack, Djerf-Pierre, and
Shehata (2013).
2. Given the large number of independent variables involved in this study and the long time-
lag between waves (four months), we expected relatively small relationships. We therefore
needed large sample and subsample sizes. These first two waves of the project are larger,
more demographically diverse, and less subject to attrition.
3. Although it should be recalled that the relationship was non-significant in the fully
controlled autoregressive model (see results).
The authors are grateful to all members of the Media Innovation Lab (University of Vienna) for
their help with the data collection for this study.
Disclosure Statement
There is no conflict of interest in relation to this article.
The second author is funded by the Viera y ClavijoProgram from the Agencia Canaria de
on, Innovaci
on y Sociedad de la Informaci
on and the Universidad de La Laguna.
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... For intentional news avoidance, previous research also shows a negative association: the less people trust professional news, the more they actively avoid the news (Goyanes et al., 2021;Toff & Kalogeropoulos, 2020). However, this relationship is less strong and depends on the type of modeling (Goyanes et al., 2021). ...
... For intentional news avoidance, previous research also shows a negative association: the less people trust professional news, the more they actively avoid the news (Goyanes et al., 2021;Toff & Kalogeropoulos, 2020). However, this relationship is less strong and depends on the type of modeling (Goyanes et al., 2021). Research on intentional news avoidance during COVID-19 in the UK shows that 32% (May 2020) and 34% (July 2020) of the people who state that they sometimes or often actively avoid the news during the pandemic do so because they lack trust in the news . ...
... In line with that finding, Edgerly (2021) shows that political interest makes it less likely to use very little or no news at all. For intentional news avoidance, political interest also has a negative effect (Goyanes et al., 2021). ...
Full-text available
Intentional news avoidance describes an intermittent news use practice in which people deliberately turn away from the news. First findings point out that the level of intentional news avoidance has increased since the COVID-19 pandemic. Since this might be related to negative consequences both with regard to compliance with measures and for the economic situation of journalism, the current study empirically investigates the prevalence and predictors of intentional news avoidance during COVID-19. For this purpose, we analyze two waves (April 2020 n = 1459, May 2020 n = 1433) of the Austrian Corona Panel that include relevant measures for news avoidance and potential predictors. Our findings show that the vast majority of the participants at least sometimes avoids news about COVID-19 (75% in April and 80% in May). This behavior can be explained with a lack of trust in news about COVID-19 and negative emotional responses to news (e.g., information overload or emotional distress). In sum, the high prevalence of news avoidance can be considered a result of the general burden of the pandemic, but also dissatisfaction with the role of the media.
... The consequences of information overloading include stress, anxiety, and exhaustion which have been identified by researchers; hence, the need for social media news avoidance evolves (Wang et al., 2022). The individuals feel tired while processing and analyzing a large amount of information acquired from different sources to unearth relevant information (Goyanes et al., 2021a). Van Erkel and Van Aelst (2020) studied the outcome of excessive Frontiers in Psychology | ...
... The users gain more knowledge through social media as compared to traditional news media; hence, their need for news is fulfilled through social media. Theoretically, individuals with a higher need for news may experience unpleasant news on social media that might influence them negatively; hence, they indulge in social media news avoidance behaviors (Goyanes et al., 2021a). These users are less exposed to traditional news channels; therefore, they are unable to fully understand the news content (Momsen and Ohndorf, 2022). ...
... The plausible reason could be a higher need for news develops social media news avoidance behavior among people because they require only reliable and credible news. Goyanes et al. (2021a) found similar results. However, the fifth hypothesis of the study was rejected indicating that need for news has no effect on social media news filtering among social media users. ...
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In the present era of information technology, people tend to seek out news to enhance their current knowledge and awareness and to gain literacy. The reliance on seeking out news and relevant information has become very necessary to accomplish personal and organizational objectives. The present study has undertaken an inquiry to investigate the impact of social media news overload on news avoidance and news filtering with the mediating and moderating mechanisms of the need for news and media literacy, respectively. For this purpose, data were obtained from 358 Chinese social media users through the aid of survey forms. The data obtained were then analyzed through Smart-PLS software. The statistical technique used for analysis is structural equation modeling (SEM) to determine the validity of the proposed hypotheses. The results of the study indicated that social media news overload has a significant effect on news avoidance, the need for news, and news filtering behavior. It was also observed that the need for news had a significant impact on news avoidance. In addition to this, it was also revealed that the need for news significantly mediated the relationship between social media news overload and news avoidance; however, it did not mediate the relationship between social media news overload and news filtering. Lastly, it was identified that media literacy significantly moderated the relationship between the need for news and news avoidance and it did not moderate the relationship between the need for news and news filtering behavior. This study has made important theoretical contributions by advancing the current literature in terms of the empirical evidence that indicates a significant relationship between social media news overload, news avoidance, and news filtering. Practically, this study contributed by emphasizing the need to encourage and train people to use strategies to seek relevant news in a vast repository of information available through information technology.
... However, while from a normative democratic perspective news avoidance is conceptualized as negative, there is also scholarly debate on potential positive consequences of news avoidance such as increased mental wellbeing (de Bruin et al., 2021). News avoidance can thus serve as a coping strategy (Goyanes et al., 2021). ...
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Previous research has mostly ignored that citizens could experience information overload from a single issue extensively covered in the news. Especially when it comes to issues upon which citizens decide directly in a referendum, overload and avoidance would be problematic from a democracy theory perspective. This study investigates overload and avoidance at the issue level based on a three-wave panel survey on a referendum in Switzerland and finds weak information overload at the aggregate level. However, citizens become increasingly overloaded during the period of extensive news coverage which leads to avoidance of news on the issue but not of interpersonal discussions.
... Scholars have proposed that news avoidance can be remedied by increasing news efficacy (Park, 2019), interest in politics, and trust in professional news (Goyanes et al., 2021). In addition to these individual-level factors, our study offers newsroom diversity as a possible solution. ...
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News avoidance, particularly among women, raises potential challenges for democracy. While research shows audiences don’t penalize women reporters or the outlets that employ them, we don’t know whether the presence of women in the newsroom affects such avoidance behaviors, particularly for women audiences. Additionally, the news may communicate gender to the audience in other ways beyond ascriptive characteristics of the reporter. We ask, do reporter gender, source gender, and gender of issues affect readers’ engagements with news, attitudes toward news avoidance, or perceptions about gender bias in journalism? Results from a survey experiment show that newsroom diversity affects “news-is-for-men” perceptions. Upon reading a masculine-issue story, respondents—both men and women—were more willing to read and seek stories from the same news outlet. News stories from male reporters also caused a stronger belief that the newsroom was dominated by men, which boosted “news-is-for-men” perceptions. As such, though reporter gender may not always impact readers directly, its influence is more pervasive than can be directly captured.
... It is well established that politically interested users consume more news, search for them more actively, and know more about politics than those with lower political interest (e.g., Möller et al., 2020;Shehata & Strömbäck, 2021;Strömbäck & Shehata, 2010). Conversely, low political interest is associated with sparse news use, increased news avoidance, and lower levels of political knowledge (e.g., Boukes, 2019;Goyanes et al., 2021). Additionally, research shows that the news-finds-me perception (the belief that one can be informed without actively using news) is more prevalent among the less politically interested (Gil de Zúñiga & Diehl, 2019; C. S. Park, 2019). ...
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In recent years, much research has—more or less candidly—asked whether the use of social media platforms is “making us dumber” (Cacciatore et al., 2018). Likewise, discussions around constructs such as the news-finds-me perception or illusions of knowledge point to concerns about social media users being inadequately informed. This assessment of inadequacy, explicitly or implicitly, builds on the ideal of the informed citizen with a broad interest in current affairs who knows about all important societal issues. However, research has largely ignored what citizens themselves understand as “being informed.” Accordingly, this research project asks what people actually want to be informed about, which user characteristics predict different self-concepts of informedness, and how both of these aspects relate to feelings of being informed in the context of social media platforms. Based on a preregistered, national representative survey of German social media users ( n = 1,091), we find that keeping up with news and political information is generally less important for people than staying informed about their personal interests and their social environment. However, feelings of being informed through social media are most strongly predicted by how suitable a given social media platform is perceived to be for keeping up-to-date with current affairs. This suggests that while information needs are diverse and related to different sociodemographic and personal characteristics, most people indeed seem to associate “being informed” with political information and news.
... In other words, when consumers consumed news via digital devices, they felt a higher news overload (Goyanes et al., 2021). The quantity of information is not always seen negatively because it presents information searchers with more options (Lee and Hong, 2021). ...
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In this global village, easy access to news has resulted in many changes in the preferences and patterns of people for accessing news. Therefore, the present study has attempted to investigate the effects of news relevance, perceived quality, and news overloading on people’s news curation preferences. This study has also examined the mediating role of news avoidance between the news relevance, perceived quality, and news overloading on the news curation. A quantitative technique has been employed to check the relationships proposed in the study. A sample size of 217 has been analyzed to check these hypotheses. The findings of the study revealed that news relevance has a negative impact while news overload positively and significantly impact the news curation. However, the news avoidance only mediated the relationship of news quality and news curation. Theoretically, the study has contributed to the literature of journalism and social media by finding that relevance of news has a negative significant impact on the news curation behavior of people, such that if they do not find the news relevant, they happily curate it. Practically, the study implies that the people are more prone to the quality of news rather than quantity; therefore, it is important for the news agencies to ensure that they produce and deliver the quality based news considering the accuracy to penetrate the Theoretic lass level.
In the information age we live in, we are constantly threatened by being drowned in a huge flood of information. Information overload (IO) describes this state where information can no longer be adequately processed by an individual. However, the danger posed by IO to individuals as well as organizations can still not be assessed properly due to a missing integration of previous findings. In this quantitative meta-analysis, we analysed the data of 133.011 people within 117 studies, and overall, 330 effect sizes. We performed multi-level as well as robust variance estimation analyses and found, among other things, positive correlations between IO and information avoidance, stress states, burnout and fatigue, and negative correlations between IO and performance and satisfaction. Explorative subgroup analyses revealed different moderating effects based on different vocational settings. Overall, the results of this meta-analysis indicate a negative relationship between IO and peoples’ behaviour and experience, which call for an evaluation of the exchange and handling of information. Across a wide range of studies and contexts, this meta-analysis reveals that IO may provoke the information fatigue syndrome that has been poorly considered to date, leading to severe consequences in both work and home contexts.
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Prior literature on political filter bubbles suggests an overall positive association between social media use and political networks diversification. Sometimes, this might not be the case. This study argues that the News Finds Me perception (NFM) or the belief that “one” can be well-informed about public affairs without actively seeking information as news will find “me” through “my” networks, tend to nurture a positive attitude toward algorithmic news gatekeeping. Likewise, NFM’s news over-reliance on one’s social network support the development of homogeneous information and discussion political networks in social media (political homophily). Results based on a variety of ordinary least squares regression models (cross-sectional, lagged, and autoregressive) from a U.S. representative panel survey, as we all as autoregressive structural equation model tests, indicate that this is indeed the case. This study serves to specifically clarify when and how social media and the NFM facilitate politically homogeneous filter bubbles.
This study sought to examine the potential role of news avoidance in belief in COVID-19 misinformation. Using two-wave panel survey data in Singapore, we found that information overload is associated with news fatigue as well as with difficulty in analyzing information. News fatigue and analysis paralysis also subsequently led to news avoidance, which increased belief in COVID-19 misinformation. However, this link is present only among those who are frequently exposed to misinformation about COVID-19.
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There is a vast research tradition examining the antecedents that lead people to be politically persuaded. However, political opinion and attitude change in social media has received comparatively scarce attention. This study seeks to shed light on this strand of the literature by theoretically advancing and empirically testing a structural equation model linking online social media, and fake news exposure, with political discussion and political persuasion in social media. Drawing on autoregressive causal tests from two waves of US survey panel data collected in 2019 and 2020, our results indicate that online, social media fake news, and political discussion are all positive predictors of individual political attitude change. Furthermore, structural equation tests reveal that online and social media news lead individuals to be exposed to fake news, which, in turn, predict higher levels of political discussion, ultimately facilitating political persuasion in the social media realm. Limitations and further suggestions for future research are also included in the study.
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This study examines the causal effects of social media use on political knowledge as well as the underlying mechanisms through which such an effect occurs. The findings suggest that social media use hinders rather than enhances an individual’s learning about politics, because social media use fosters the perception that one no longer needs to actively seek news in order to stay informed (i.e., news-finds-me perception), and this in turn may have an adverse effect on an individual’s learning about politics. However, those who use traditional forms of media to a substantial degree to complement their news consumption via social media are less negatively affected than those who do not.
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The ubiquitous nature of online news, especially in social media, increasingly exposes readers to news even when they are not seeking it. Based on 50 semi-structured interviews with Spanish incidental news consumers, we inductively explore the effects of incidental news consumption and problematize the phenomenology of encountering news passively on social media. Our results first question previous quantitative analysis on the potential positive effects of incidental news exposure, evidencing its minimal or null effects on how citizens make sense of, and are informed about, public affairs and politics. Second, our findings indicate that citizens appraisals of incidental news content varies according to the producers involved, the topics addressed and the interest triggered. Our study contributes to current discussions of incidental news exposure, arguing that both quantitative and qualitative studies should consider the direct and indirect impact of structural, cognitive and situational variables to holistically account for incidental news effects.
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The main social media platforms have been implementing strategies to minimize fake news dissemination. These include identifying, labeling, and penalizing –via news feed ranking algorithms– fake publications. Part of the rationale behind this approach is that the negative effects of fake content arise only when social media users are deceived. Once debunked, fake posts and news stories should therefore become harmless. Unfortunately, the literature shows that the effects of misinformation are more complex and tend to persist and even backfire after correction. Furthermore, we still do not know much about how social media users evaluate content that has been fact-checked and flagged as false. More worryingly, previous findings suggest that some people may intentionally share made up news on social media, although their motivations are not fully explained. To better understand users’ interaction with social media content identified or recognized as false, we analyze qualitative and quantitative data from five focus groups and a sub-national online survey (N = 350). Findings suggest that the label of ‘false news’ plays a role –although not necessarily central– in social media users’ evaluation of the content and their decision (not) to share it. Some participants showed distrust in fact-checkers and lack of knowledge about the fact-checking process. We also found that fake news sharing is a two-dimensional phenomenon that includes intentional and unintentional behaviors. We discuss some of the reasons why some of social media users may choose to distribute fake news content intentionally.
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Today, people are exposed to vast information flows while online or on social media. This abundance has led some people to believe that they no longer have to actively seek the news to be well informed about public affairs and that important news will find them through social media or other online channels. Recently, academics have offered a first theoretical account, capturing this belief as the “news finds me” perception (NFM). Initial studies have been conducted in the U.S. and Austria, indicating deleterious effects between NFM and both traditional news use and political predispositions and behaviors. This study seeks to expand this line of research, exploring the proliferation of NFM in 10 societies around the world. Findings give further insights into the degree of NFM proliferation in diverse contexts. Across societies, NFM is associated with age, social media news use, and other meaningful democratic variables such as political interest, political knowledge, and voting behavior.
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Social media is an important source of news and information in the United States. But during the 2016 US presidential election, social media platforms emerged as a breeding ground for influence campaigns, conspiracy, and alternative media. Anecdotally, the nature of political news and information evolved over time, but political communication researchers have yet to develop a comprehensive, grounded, internally consistent typology of the types of sources shared. Rather than chasing a definition of what is popularly known as “fake news,” we produce a grounded typology of what users actually shared and apply rigorous coding and content analysis to define the phenomenon. To understand what social media users are sharing, we analyzed large volumes of political conversations that took place on Twitter during the 2016 presidential campaign and the 2018 State of the Union address in the United States. We developed the concept of “junk news,” which refers to sources that deliberately publish misleading, deceptive, or incorrect information packaged as real news. First, we found a 1:1 ratio of junk news to professionally produced news and information shared by users during the US election in 2016, a ratio that had improved by the State of the Union address in 2018. Second, we discovered that amplifier accounts drove a consistently higher proportion of political communication during the presidential election but accounted for only marginal quantities of traffic during the State of the Union address. Finally, we found that some of the most important units of analysis for general political theory—parties, the state, and policy experts—generated only a fraction of the political communication.
In today’s media environment, there are increased opportunities to consume news in various formats and styles. Why then, do some people say they consume little to no news? The focus of this study is to identify the factors related to extremely low levels of news consumption. Survey data from a nationally representative sample of U.S. adults is used to test different explanations for news avoidance. Results point to several factors that explain lower overall levels of news consumption. Extremely low news consumption is related to a disinterest in politics, perceptions of news lacking relevance, low news self-efficacy and a lack of knowledge about the news system. Perhaps surprisingly, the emotional toll of news (e.g. news fatigue, upset feelings) did not explain variation in overall levels of news consumption. Based on these findings, efforts to convert news avoiders into more regular consumers of news is discussed.
In a fragmented digital media environment where news is increasingly encountered passively in social media feeds and via automated mobile alerts, active avoidance of news, rather than deliberate consumption, takes on outsized importance in shaping what it means to be an informed citizen. This article systematically evaluates the factors that predict news avoidance behaviors, considering both individual- and country-level explanations. Using a large-scale quantitative, comparative approach, we examine more than 67,000 survey respondents across 35 countries worldwide and find consistent evidence for how factors including demographics, political attitudes, and news genre preferences shape avoidance consistently across information environments. But we also show how country-level contextual factors, what we call “cultures of news consumption,” influence behaviors beyond that which is explained by respondent-level differences. Specifically, levels of press freedom and political freedom and stability are shown to negatively predict rates of news avoidance. These findings suggest that many people’s news use practices depend not only on personal characteristics and preferences but quite sensibly on the news available to them, which they may have good reason to view as deficient or untrustworthy, as well as culturally specific norms around its value and utility.
News avoidance is considered an increasing problem for the news industry and democracy at large. As news companies lose consumers, democracy loses the informed foundation for an engaged citizenry. Meanwhile, research on news avoidance is hampered by the lack of a common understanding of the phenomenon. In this conceptual study, we first review and discuss extant conceptualizations and operationalisations of news avoidance. Second, we present a model distinguishing two types of news avoidance—intentional and unintentional—depending on the underlying causes leading people to tune out. Third, we argue that different solutions apply to the two types of news avoidance. To engage intentional news avoiders, the news selection and news presentation must to be changed. To engage unintentional news avoiders, the opportunity structures provided in the media system must be more favourable towards inadvertent news exposure.