Content uploaded by Bingbing Zhang
Author content
All content in this area was uploaded by Bingbing Zhang on Dec 22, 2024
Content may be subject to copyright.
Warning Concerning Copyright Restrictions
The copyright law of the United States (Title 17, United States Code) governs the
making of photocopies or other reproductions of copyrighted material.
Under certain conditions specied in the law, libraries and archives are authorized
to furnish a photocopy or other reproduction. One of these specied conditions is
that the photocopy or reproduction is not to be “used for any purpose other than
private study, scholarship, or research.” If a user makes a request for, or later uses, a
photocopy or reproduction for purposes in excess of “fair use”, that user may be liable
for copyright infringement.
This institution reserves the right to refuse to accept a copy order if, in its judgment,
fulllment of the order would involve violation of copyright law.
This document was provided to you on behalf of The University of Iowa Libraries.
Thank you for using the Interlibrary Loan or Article Delivery Service.
Finding “fake”in the news:
the relationship between social
media use, political knowledge,
epistemic political efficacy and
fake news literacy
Bingbing Zhang
School of Journalism and Mass Communication, University of Iowa,
Iowa City, Iowa, USA
Avery E. Holton
Department of Communication, University of Utah, Salt Lake City, Utah, USA, and
Homero Gil de Z
u~
niga
Democracy Research Unit (DRU), University of Salamanca, Salamanca, Spain and
Pennsylvania State University, University Park, Pennsylvania, USA
Abstract
Purpose –In the past few years, research focusing on misinformation, referred to broadly as fake news, has
experienced revived attention. Past studies have focused on explaining the ways in which people correct it
online and on social media. However, fewer studies have dealt with the ways in which people are able to
identify fake news (i.e. fake news literacy). This study contributes to the latter by theoretically connect
people’s general social media use, political knowledge and political epistemic efficacy with individuals’fake
news literacy levels.
Design/methodology/approach –A diverse and representative two-wave panel survey in the United States
was conducted (June 2019 for Wave 1, October 2019 for Wave 2). We performed cross-sectional, lagged and
autoregressive regression analyses to examined how social media us, people’s political knowledge and political
epistemic efficacy are related to their fake news literacy.
Findings –Results suggest that the more people used social media, were politically knowledgeable and
considered they were able to find the truth in politics (i.e. epistemic political efficacy), the more likely they were
to discern whether the news is fake. Implications of helping media outlets and policy makers be better
positioned to provide the public with corrective action mechanisms in the struggle against fake news are
discussed.
Research limitations/implications –The measurement instrument employed in the study relies on
subjects’self-assessment, as opposed to unobtrusive trace (big) digital data, which may not completely capture
the nuances of people’s social media news behaviors.
Practical implications –This study sheds light on how the way people understand politics and gain
confidence in finding political truth may be key elements when confronting and discerning fake news. With
the help of these results, journalists, media outlets and policymakers may be better positioned to provide
citizens with efficient, preemptive and corrective action mechanismsin the struggle against misinformation.
Originality/value –Recent literature highlights the importance of literacy education to contest fake news, but
little is known about what specific mechanisms would contribute to foster and reinvigorate people’s fake news
literacy. This study helps address this gap.
OIR
48,7
1470
Funding: This work has benefited from the support of the Spanish National Research Agency’s Program
for the Generation of Knowledge and the Scientific and Technological Strengthening
Research þDevelopment Grant PID2020-115562GB-I00. The last author is funded by the ‘Beatriz
Galindo Program’from the Spanish Ministry of Science, Innovation and Universities, and the Junta de
Castilla y Le
on.
Responsibility for the information and views set out in this study lies entirely with the authors.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1468-4527.htm
Received 5 March 2024
Revised 22 May 2024
Accepted 18 June 2024
Online Information Review
Vol. 48 No. 7, 2024
pp. 1470-1487
© Emerald Publishing Limited
1468-4527
DOI 10.1108/OIR-03-2024-0140
Peer review –The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-
03-2024-0140
Keywords Misinformation, Political epistemic efficacy, Social media use, Fake news literacy,
Two-wave panel survey
Paper type Research paper
The 2024 US presidential election is already capturing significant controversy surrounding
political candidates and their campaigns, as they faced allegations of utilizing artificial
intelligence to propagate misinformation, commonly referred to as “fake news,”through
various news and social media channels. For example, this issue emerged when voters
received deceptive Biden robocalls, aiming to dissuade them from participating in the
primary election (Astor, 2024). Such actions involving individuals who have little or no
professional connections to, or credentials for, the creation and dispersion of critical factual
news and information comes as part of a growing trend to use multiple forms of fake news to
challenge and change public perceptions and opinions and to, in some cases, drive political
and other agendas (see McGregor, 2020;Tandoc et al., 2017). This highlights the concern some
media scholars have expressed over the news media’s–and relatedly, social media platforms’
–failure to adjudicate political news and information (Pingree et al., 2012). That is, when there
is a clear and knowable truth, the news media should signal that without providing balanced
coverage of fake news that attempts to counter such truth. Yet, examples like that of Biden
robocalls have raised questions about the public’s ability to discern fact from fiction, even
when presented with information to back up truthful news coverage.
This “infodemic,”which was equally highlighted during the initial stages of the global
COVID-19 outbreak, has drawn considerable concern from public officials and journalists
alike (Zimmer, 2020). Collectively, news media scholars and organizations across the globe
such as Comprobado, CrossCheck Australia/France/Nigeria/United Kingdom and Maldita.es
(see First Draft News, 2021;Tandoc et al., 2017) have worked to better understand the
motivations behind the creation and dissemination of fake news, misinformation and hoaxes,
which are frequently of a political nature or are meant to polarize individuals around political
beliefs.
As scholars behind these and related efforts have noted, the increasing amount of fake
news moving across social media platforms –and now through information created by
artificial intelligence (AI) –makes discerning fact from fiction difficult for individuals and
raises questions about how exactly they can improve their own confidence in and ability to
identify fake news (Paisana et al., 2020;Schwarzenegger, 2020). Helping people recognize
what exactly fake news is, how to detect it and what do to with it may help them feel more
confident in their interactions with misinformation as well as information that is factual
(Vraga et al., 2020;Hinsley and Holton, 2021). Equally, understanding the role people’s
confidence in understanding and determining truth in political coverage termed by some
scholars as epistemic political efficacy –plays in their fake news literacy may signal a pathway
to addressing, quelling and possibly preventing the spread of fake news (Pingree, 2011;
Pingree et al., 2012).
Individuals’confidence in their ability to recognize fake news may be related to the ways
in which they think about and interact with the news (Schwarzenegger, 2020). Thus, the more
people think about the news and are self-reflective in the ways they interact with the news on
digital and social media platforms, the more confident they may feel in their ability to tell fact
from fiction in those spaces. This, combined with measures of confidence such as those
offered through research using epistemic political efficacy (Pingree, 2011;Pingree et al., 2012),
may help to explain, at least in part, peoples’fake news literacy –individuals’ability to identify
Online
Information
Review
1471
fake news from real news and the degree of familiarity and confidence people have in
detecting fake news (Ferrucci and Hopp, 2023;Schmeichel et al., 2018). Political knowledge is
positively related to cognitive elaboration of factual information about news and public
affairs (Eveland, 2001;Vraga and Tully, 2019) which also should improve fake news literacy.
Thus, this study considers the possible role of people’s frequency of social media use, as well
as the possibly related roles of political knowledge and epistemic political efficacy may play
in fake news literacy.
Through a diverse and generally representative two-wave panel data in the United States
(US), and relying on different OLS regression strategies, this study reveals that social media use
and people’s political knowledge are positive and direct predictors of their fake news literacy.
Also, importantly, epistemic political efficacy plays a moderating role in building fake news
literacy skills. That is, for the most part when people spend more time using social media, it
helps them to better identify fake news directly, however, for those who use social media less
often, epistemically finding truth in politics drastically helps them to better identify fake news.
Fake news literacy and social media
While engagement with fake news may be a willful or unintentional act, the consequences are
sharply negative in most cases (Borah and Lorenzano, 2023). Fake news has become
embedded in social media platforms, which began addressing its impacts more publicly and
through more regulation and policy (Molina et al., 2021). Twitter, Facebook, Instagram and
TikTok all began searching for and flagging fake news and its creators, and in many cases,
its sharers as well, removing some content and banning thousands of users along the way,
including the then-president of the United States (Denham, 2021). This action seemed to
answer the call of many media scholars and practitioners who had for several years argued
for more regulation of social media content and information, particularly fake news, given its
observable and measurable impacts on individuals, businesses, communities and political
processes (Hinsley and Holton, 2021;Tandoc et al., 2018a,b).
As Wardle (2017) argued, fact and fiction have blurred social media spaces to the point
where technologies such as artificial intelligence and deep fake content now sometimes seem
more authentic than the truth. This at a time when social media users –more than 3.5 billion
of them globally and counting –encounter misinformation, false and misleading content, and
fake news in a variety of formats and across a multitude of digital and social media platforms
according to Pew Research Center (2019). More than half of people who use social media for
news said they understand fake news as part of the content stream they will encounter
(Shearer and Mitchell, 2021), suggesting that as people are exposed to more fake news, they
may normalize as part of their active professional news engagement routines (Tandoc et al.,
2017). They may indeed encounter fake news, but because they see more and more of it, they
know what it looks like and what cues to search for when determining truthful news from its
fictional counterpart (Hinsley and Holton, 2021). Furthermore, the identification of
misinformation through flagging and the implementation of accuracy warnings on social
media could enhance people’s literacy regarding news quality, reducing the likelihood of
misinformation dissemination (Pennycook and Rand, 2022). Enhancing one’s self-perceived
media literacy has been shown to mitigate the negative effects of misinformation by
bolstering their capacity to identify it in subsequent encounters (Borah and Lorenzano, 2023;
Su et al., 2022). Research indicates that higher levels of news media literacy foster skepticism
towards news content, consequently promoting corrective actions against misinformation
(Xiao and Yang, 2023). Hence, it is crucial to explore the factors that could enhance
individuals’proficiency in discerning fake news.
Viewing news content on social media has been found to contribute to the development of
news literacy (Vraga and Tully, 2019), so it would stand to reason that the more frequently
OIR
48,7
1472
individuals consume social media, and the more likely they are to encounter fake news
alongside truthful news, their fake news literacy could also benefit. Although previous
research has defined news literacy as the awareness of news production and the influence of
news on users and producers which is connected to civic engagement (Maksl et al., 2017),
neither a definition, operationalization, nor a test for fake news literacy has been developed.
Thus, we build on news literacy and its connection to social media engagement by offering
first our definition of fake news literacy as individuals’ability to discern fake news from real
news and then use a previously validated news media literacy scale to operationalize it
(Schmeichel et al., 2018). We also acknowledge that this measure can only capture those who
knows fake news but not those who believe in falsehood. Building in this line of research, we
also propose that the more frequently individuals consume social media, they will have
higher opportunities to encounter news content (Tewksbury et al., 2001) and also fake news
online, which could cultivate the ability to identify fake news from real news.
H1. Social media use will be positively associated to fake news literacy.
Political knowledge and fake news literacy
Previous research has identified major predictors for news literacy including news exposure
and consumption behaviors, knowledge level, personal locus and control of media such as
need for cognition (Maksl et al., 2015), and trust and skepticism of media content (Vraga et al.,
2015). People may build trust in the news and improve their news literacy by fact-checking,
verifying sources of news content as well as comments connected to that content on social
media, or searching for cues within news content that help build their news knowledge and
discern fact from opinion (Huber et al., 2021;Jun et al., 2017). News literacy and the confidence
built from it may also help people be savvier when encountering fake news (Paisana et al.,
2020;Quintanilha et al., 2019), signaling again the possible significance of fake news literacy
and other individual efficacies that may be related to it.
For example, individuals who show a superior level of political sophistication and
knowledge tend to have more systematic tools to understand, process and act on news
content (Amazeen and Bucy, 2019;Eveland, 2001). Knowledge and skills are essential
elements when conceptualizing news literacy (Vraga and Tully, 2019), and knowledge
broadly plays an important role in identifying misinformation (Amazeen and Bucy, 2019).
Those people who have more political knowledge tend to be more thoughtful and critical
about the news. The cognitive mediation model showed that those people who engaged in
elaborative processing when viewing news content had higher political knowledge, which
indicated the positive correlation of elaboration and political knowledge (Eveland, 2001;Park
and Kaye, 2019). With that in mind, it stands to reason that politically knowledgeable people
have more experience and engage in more elaborative processing when they are exposed to
fake news as well. Thus, they should be more capable in identifying fake news.
H2. Individuals’political knowledge will be positively associated to higher levels of fake
news literacy.
Epistemic political efficacy and fake news literacy
The association between political efficacy and news literacy has been investigated, indicating
a positive relationship (e.g. Tully and Vraga, 2018). However, previous research has tested the
internal political efficacy addressing the confidence in one’s own ability in affecting politics or
political change and external political efficacy referring to confidence in the governments’
responses to the publics’request (Craig and Maggiotto, 1982;Gil de Z
u~
niga et al., 2017).
This leaves room to explore epistemic political efficacy more thoroughly –confidence in one’s
Online
Information
Review
1473
own ability to understand and determine the truth about factual aspects of politics (Pingree,
2011;Pingree et al., 2012)–and its possible association with fake news literacy.
As a relatively new but important concept, research has shown that epistemic political
efficacy can help people discern the truth in news and improve overall news literacy (e.g.
Ferrucci and Hopp, 2023;Vraga and Tully, 2019). News content, and especially politically
oriented content, has been criticized for giving voice to false information by attempting to
balance coverage or avoid bias by providing perspectives from all political parties even in the
face of competing truths (Jamieson and Waldman, 2003;Pingree, 2011). Such tactics can be
detrimental to news consumers trying to make sense of complex or partisan issues, causing
them to at once question the coverage they encounter as well as their own ability to
understand what is true and what is false (Pingree, 2011). But heightened epistemic political
efficacy can help counter problematic coverage and potentially empower individuals to
understand and value truth in the news coverage they engage with. Epistemic efficacy can
help improve understanding of a broad array of audience behaviors including information
seeking, political knowledge production and sharing, and opinion formation (Pingree, 2011).
In broad terms, self-efficacy theory suggests that people may choose what information to
seek and what information to avoid based on how confident they are in finding and
processing such information (Farman et al., 2018).
Epistemic political efficacy traces a similar thought, suggesting that the more people believe
in their ability to find and understand political news and information (i.e. confidence), the more
likely they may be to engage inseeking out such information and deepening their engagement
with it (Pingree, 2011;Pingree et al., 2012;York et al., 2020).Yo rk et al. (2020) found that exposure
to fact-checkers of misinformation could increase epistemic political efficacy and vice versa,
hinting at the role of epistemic political efficacy in acknowledging fake news and the processes
applied to address it. However, how exactly epistemic political efficacy is associated to fake
news literacy, if at all, has not been fully explored. Recent research has shown a correlation
between increased epistemic political efficacy and individuals’capacity to recognize inaccurate
fake news (Ferrucci and Hopp, 2023). Those possessing a higher level of epistemic efficacy were
more adept at discerning fake news (Hopp, 2022). Additionally, fake news literacy, defined as
the perception of one’s ability to identify fake news, was found to align with actual abilities in
discerning fake news (Hopp, 2022). Consequently, it is crucial to explore strategies aimed at
enhancing fake news literacy. We thus build on existing research and continue exploring the
relationship of these two theoretical concepts by hypothesizing:
H3. Epistemic political efficacy will be positively associated to fake news literacy.
Moderation role of epistemic political efficacy
Much of the research explored here relies on or acknowledges the proliferation of fake news
across social media platforms, the effects of social media use and the possible moderating role
of epistemic political efficacy should also be considered. Social media use is associated with
increases in news literacy as well as in confidence to identify fake news on social media
platforms (Paisana et al., 2020;Schwarzenegger, 2020). First, individuals who use more social
media might have higher possibilities of exposure to fake news (Allcott and Gentzkow, 2017).
Second, individuals who use social media more also may connect to more diverse social
networks, which generally increases the chances for them to expose to fake news but at the
same time also more instances of factual news incidentally (Boczkowski et al., 2018). If those
people are confident in finding truth among the news they have been exposed to, they might
develop higher fake news literacy under the same amount of social media consumption.
Overall, social media use generally increases the chances for individuals’exposure to news
that are factual or fake incidentally or intentionally (Shearer and Mitchell, 2021), providing
cues for people to discern what is “real”vs “fake”news. Thus, those who have higher level of
OIR
48,7
1474
epistemic political efficacy may have heightened more news consumption and information
seeking on social media, though the relationship could also work in reverse given that self-
efficacy broadly can help to predict engagement with social media platforms. We thus
propose the following research question to test the interaction effect of epistemic political
efficacy and social media use on fake news literacy:
RQ1. Will epistemic political efficacy moderate the relationship between social media use
and fake news literacy after controlling other factors?
Method
Sample
The data was drawn from a diverse and US representative panel survey collected for a large
research project on attitudinal and behavioral outcomes of uses of new and traditional media
across two waves (June 2019 for Wave 1, October 2019 for Wave 2). The Democracy Research
Unit at the University of Salamanca contracted IPSOS Austria to provide the subjects for the
survey which was fielded in the United States. All questions were administered via Qualtrics
at the University of Vienna. To achieve US national representativeness and pursue
generalizable inferences on the US population, IPSOS curates a massive opt-in panel of
respondents of hundreds of thousands of US individuals. They stratified a subsample of 3,000
individuals from this pool, matching key demographic elements from the US census. The
final sample left 1,338 valid cases in Wave 1, yielding a cooperation rate of 45.5% (AAPOR,
2011) and 511 valid cases in Wave 2, yielding a cooperation rate of 40.9% (AAPOR, 2011). In
other words, the final sample includes 1849 responses, of which 1,338 responded to Wave 1
and 511 out of 1,338 responded to Wave 2.
Measures
Criterion variable. Fake news literacy. The dependent variable was measured drawing on
a validated scale on news media literacy (Schmeichel et al., 2018). This construct seeks to
capture the degree of familiarity subjects have when presented with fake news content.
Respondents were asked how much they agree (1 5strongly disagree;105strongly agree)to
the following statements including: (a) Generally, I am able to discern fake news from real
news; (b) Most of the times, when I see fake news, I am able to detect them easily; and (c) It is
very unlikely that a piece of fake news can mislead me. The three items were combined into an
index and checked the reliability (W
1
Cronbach’s
α
50.86; M56.04; SD 52.33; W
2
Cronbach’s
α
50.87; M56.36; SD 52.18).
Independent variables. Social media use. Based on scale from Correa et al. (2010) and
Kim et al. (2013), this concept measured the extent of using social media. Respondents were
asked to answer the following question (1 5not at all;105a great deal): On a typical day, how
much do you use social media? (W
1
M56.19; SD 52.94).
Political knowledge. Based on previous measures on knowledge of political issues and public
affairs (Carpini and Keeter, 1996), a scale was used to assess respondents’awareness of current
political issues. Respondents were asked to answer eight questions to indicate their political
knowledge. For example, they were asked the following questions (0 5incorrect or don’tknow;
15correct) including: (a) For how many years is a United States Senator elected –that is, how
many years are there in one full term of office for a US Senator? (2,4,6,8, Don’t know); and (b) On
which of the following does the US federal government currently spend the least? (Foreign aid,
Medicare, National defense, Social Security, Don’t know). The score for these eight questions were
combined into an index and ensured the reliability (W
1
Cronbach’s
α
50.71; M52.77; SD 52.03).
Epistemic political efficacy. This construct was adapted from an instrument measuring
epistemic political efficacy (Pingree, 2011), a 3-item scale was used to measure respondents’
Online
Information
Review
1475
self-confidence in finding truth in politics. Respondents were asked to rate their agreement to
the following statements (1 5strongly disagree;105strongly agree): (a) I feel confident that
I can find the truth about political issues; (b) If I wanted to, I could figure out the fact behind
most political disputes; and (c) There are objective facts behind most political disputes, and if
you try hard enough you can find them. These three items were combined into an index and
ensured the reliability (W
1
Cronbach’s
α
50.89; M56.19; SD 52.15).
Control variables. Fake news exposure. A 3-item scale was used to assess the frequency
subjects expose to fake news content (Huber et al., 2021). Respondents were asked to report
how often (1 5never to 10 5all the time) they have seen (a) fabricated information that
mimics news media content and could mislead readers, (b) articles that originate from
satirical websites but were transformed by others and put in a misleading and (c) stories
containing deliberatively misleading elements making the reader believe it is correct.
The three items were combined into an index and checked the reliability (W
1
Cronbach’s
α
50.88; M56.04; SD 52.33).
Political interest. This construct taps subjects’overall interest in politics and current
affairs (Lupia and Philpot, 2005;Verba and Nie, 1987) by including the following two
questions (1 5not at all;105a great deal): (a) how interested you are in information about
what is going on in politics and public affairs? And (b) how closely you pay attention to
information about what’s going on in politics and public affairs? The two items were
combined into an index that yielded a robust reliability Spearman-Brown coefficient (W
1
Spearman-Brown
ρ
50.90; M56.13; SD 52.72).
Online news use. Adapted from Lee et al. (2023), this construct taps on the news
consumption behaviors through online media. Respondents were asked in the past month
how often (1 5never to 10 5all the time) they got news from the following media sources
including: (a) online news sites (e.g. Politico, VOX, BuzzFeed); (b) Citizen journalism sites (e.g.
GroundReport, CNN’s iReport); and (c) local news online sites (online sites related to news in
your local community). Three averaged items were included in a unique index (W
1
Cronbach’s
α
50.68‚M53.81‚SD 52.30).
Traditional media news consumption. Adapted from Zhang et al. (2022), this construct
was measured through an index of news consumption on traditional media. Respondents
were asked to indicate how often (1 5never to 10 5all the time) in the past month they got
news from the following media sources: (a) Network TV news (e.g. ABC, CBS, NBC); (b) Local
television news (cf. local affiliate stations); (c) National newspapers (e.g. New York Times,
Washington Post, USA Today); (d) Local newspapers (e.g. Oregonian, Houston Chronicle,
The Miami Herald); (e) MSNBC cable news; (f) CNN cable news; (g) FOX cable news; and (h)
Radio news (e.g. NPR, talk shows)(W
1
Cronbach’s
α
50.88; M54.50; SD 51.91).
Social media news use. Multiple scales were used to measure the frequency with which
subjects use social media to consume news and public affairs information (Gil de Z
u~
niga et al., 2018).
Respondents were asked to indicate how often in the past month they got news from the following
sources including “local news on social media,”“national news on social media,”“Facebook,”
“Twitter,”“Snapchat,”“LinkedIn,”“WhatsApp”or “Instagram.”Additionally, respondents were
asked to think of the social media they use the most and how often they did use it to “stay informed
about current events and public affairs”,“stay informed about my local community”and “get news
about current events from mainstream media (such as CNN or ABC)”. All 11 items are measured on
a1to10Likerttypescale(15never to 10 5all the time) and combined into an index after examining
its construct reliability (W
1
Cronbach’s
α
50.91‚M53.60‚SD 52.07).
Demographics. The following demographics were also controlled in the present study:
Age (36–55: 39.7%; 23–35: 25.2%; 56 or older: 28%; 18–22 years: 7.1), gender (53.2% female),
education (high school: 31.6%; some college: 25%; Master’s degree: 15.5%; Bachelor’s degree:
11.8%; some graduate education 6.7%; professional certificate: 4%; less than high school:
3.6%; and Doctoral degree: 1.9%), and ethnicity or race (75.2% majority –white).
OIR
48,7
1476
Statistical analyses
First, a set of bivariate zero order correlations is presented to learn more about the associative
nature of all the variables of intertest in the study. Then, to formally test the hypotheses and
the research question offered in the manuscript, a series of regression analyses were
conducted. The first model reveals an associative relationship between the independent
variable of interest and the criterion variable with a cross-sectional ordinary least-squared
regression. To account for the effect of epistemic political efficacy further and more
stringently on the development of fake news literacy, a lagged and an autoregressive
ordinary least-squared regressions were also performed. The former tests a panel time
relationship without controlling for prior levels of the dependent variable in time 1 (Maxwell
et al., 2011). The latter model, however, includes the dependent variable in preceding time 1 as
key causal control of the predictions of the dependent variable in time 2. The lagged and
autoregressive regression models can help explain causal inference (Maxwell et al., 2011).
Results
First, this study includes a zero-order correlation table of all variables of control and interest
(see Table 1). Based on the zero-order correlation table, fake news literacy was positively
related to epistemic political efficacy (r50.484, p< 0.01). In addition, political knowledge was
positively associated with fake news literacy (r50.220, p< 0.01). Social media use was also
positively related to fake news literacy (r50.217, p< 0.01). As can be expected, the OLS
autoregressive regression model predicted most of the variance for any of the tested models
(ΔR
2
534.7% autoregressive; ΔR
2
522.9% lagged; ΔR
2
532.3% cross-sectional). Among
all the controls included in the study, age (β50.114, p< 0.05; panel lagged model), political
interest (β50.165, p< 0.05; cross-sectional model) and fake news exposure (β50.135,
p< 0.05; cross-sectional model) had an influence on people’s fake news literacy levels. H1
proposed that individuals who more frequently use social media broadly will also develop
higher levels of fake news literacy. The lagged and autoregressive models in Table 2 showed
a positive effect of social media use on fake news literacy (lagged: β50.123, p< 0.05;
autoregressive: β50.123, p< 0.05). However, in the cross-sectional regression model, social
media use does not predict fake news literacy (β50.024, p> 0.05). Therefore, H1 was
partially supported.
H2 hypothesized that individuals who are more knowledgeable about politics will have a
higher level of fake news literacy. All three types of regression models including cross-
sectional, lagged and autoregressive models in Table 2, showed a positive effect of political
knowledge on fake news literacy (cross-sectional: β50.070, p< 0.05; lagged: β50.137,
p< 0.05; autoregressive: β50.102, p< 0.05). Citizens who are more knowledgeable about
news and political issues, they also develop fake news literacy. Therefore, H2 was supported.
H3 proposed that individuals with higher epistemic political efficacy are more likely to
have higher levels of fake news literacy. Consistently, epistemic political efficacy has a
positive effect of political on fake news literacy in the cross-sectional analysis (β50.362,
p< 0.001, ΔR
2
59.0%), lagged regression model (β50.319, p< 0.001, ΔR
2
57.1%) and the
autoregressive model (β50.185, p< 0.001, ΔR
2
52.2%) (see Table 2). Therefore, H3 was
supported.
Finally, RQ1 asked the extent to which social media use would moderate the relationship
between epistemic political efficacy and fake news literacy after controlling other factors.
That is, the study wanted to test whether those who reported higher levels of social media use
and epistemic political efficacy also tend to be the group of people developing fake news
literacy the most. Cross-sectional, lagged and autoregressive interaction effects test in Table 3
showed that the interaction effect of social media use and epistemic political efficacy on fake
news literacy is only significantly within the cross-sectional data testing. With the aid of
Online
Information
Review
1477
12345 6 7 8 9 10111213
1 Age –
2 Education 0.20** –
3 Gender 0.14** 0.01 –
4 Race 0.33** 0.09** 0.12** –
5 Political interest 0.22** 0.25** 0.16** 0.06 –
6 Political knowledge 0.21** 0.33** 0.18** 0.10** 0.49** –
7 Fake news exposure 0.02 0.05 0.06* 0.04 0.23** 0.09** –
8 Online news use 0.23** 0.05 0.10** 0.14** 0.25** 0.02 0.21** –
9 Social media news use 0.41** 0.05 0.08** 0.23** 0.09** 0.16** 0.22** 0.65** –
10 Traditional media news use 0.01 0.10** 0.13** 0.12** 0.42** 0.07** 0.22** 0.74** 0.57** –
11 Social media use 0.23** 0.12** 0.08** 0.10** 0.02 0.14** 0.18** 0.27** 0.55** 0.19** –
12 Epistemic political efficacy
w1
0.07* 0.12** 0.21** 0.01 0.50** 0.32** 0.24** 0.23** 0.19** 0.31** 0.11** –
13 Fake news literacy
w1
0.03 0.06* 0.13** 0.01 0.39** 0.22** 0.29** 0.24** 0.22** 0.25** 0.15** 0.48** –
14 Fake news literacy
w2
0.09* 0.09 0.12** 0.04 0.32** 0.27** 0.13** 0.15** 0.13** 0.21** 0.09 0.42** 0.54**
Note(s): N51,337. Cell entries are two-tailed zero order correlation coefficients. *p< 0.05; **p< 0.01; ***p< 0.001
Source(s): Table 1 by authors
Table 1.
Zero-order Pearson’s
correlations between
variables of control and
interest
OIR
48,7
1478
Fake news literacy
(W1)
Fake news literacy (W2
Lagged)
Fake news literacy (W2
Autoregressive)
Block 1: Autoregressive term
Fake news literacy –– 0.409***
ΔR
2
29.1%
Block 1: Demographics
Age 0.045 0.114* 0.065
Education 0.018 0.002 0.011
Gender (female) 0.010 0.034 0.012
Race (white) 0.022 0.018 0.003
ΔR
2
(%) 2.5% 3.0% 0.5%
Block 2: Political attitudes
Political interest
W1
0.165*** 0.037 0.021
Political knowledge
W1
0.070* 0.137* 0.102*
ΔR
2
(%) 15.5% 10.1% 1.9%
Block 3: Media exposure
Fake news exposure
W1
0.135*** 0.045 0.008
Online news use
W1
0.065 0.001 0.000
Social media news use
W1
0.075 0.085 0.110
Traditional news
consumption
W1
0.055 0.122 0.101
Social media use
W1
0.024 0.123* 0.110*
ΔR
2
(%) 5.4% 2.6% 1.1%
Block 4
Epistemic political
efficacy
W1
0.362*** 0.319*** 0.185**
ΔR
2
(%) 9.0% 7.1% 2.2%
Total R
2
32.3% 22.9% 34.7%
Note(s): Sample size 51,338 (Wave 1); Sample size 5530 (Wave 2). Cell entries are final-entry OLS
standardized Beta (β) coefficients. *p< 0.05; **p< 0.01; ***p< 0.001
Source(s): Table 2 by authors
Fake news literacy
(Cross-sectional)
Fake news literacy
(Lagged)
Fake news literacy
(Autoregressive)
Block 1: All prior blocks Table 2
ΔR
2
32.3% 22.9% 34.7%
Block 2: Interactions
Social Media Use
W1
* Epistemic
Political Efficacy
W1
0.363 (0.000) *** 0.212 (0.190) 0.055 (0.715)
ΔR
2
0.8% 0.3% 0.1%
Total R
2
33.1% 23.2% 34.8%
Note(s): Estimates are unstandardized Beta coefficients. Standardized errors between brackets. Interaction
effects based on bootstrapping to 5,000 samples with biased corrected confidence intervals. The effects account
for the same demographic, political antecedents and media orientation control variables as found in Table 3.
Sample-W
1
51,338; Sample-W
2
5511
Source(s): Table 3 by authors
Table 2.
OLS cross-sectional,
lagged, and
autoregressive
regression models
testing epistemic
political efficacy and
fake news literacy
Table 3.
Cross-sectional, lagged,
and autoregressive
interaction effects test
Online
Information
Review
1479
PROCESS macro (Hayes, 2017), the slopes of regression lines are shown in Figure 1. When
individuals have high level of epistemic political efficacy, they were more likely to have a
higher level of fake news literacy when they use social media less. However, when individuals
have low level of epistemic political efficacy, they were more likely to have a higher level of
fake news literacy when they use social media more.
Discussion
Social media is increasingly becoming a fertile ground for the spread of misinformation where
individuals commonly encounter fake news (Allcott and Gentzkow, 2017). In this context,
some people may not be able to identify fake news because of lack of media literacy. This has
become a concerningly global phenomenon beyond US, and other Western societies (Tully
et al., 2022;Valenzuela et al., 2019). Recent literature highlights the importance of literacy
education to contest fake news (Maksl et al., 2015;Tully and Vraga, 2018), but little is known
about what specific mechanisms would contribute to foster and reinvigorate people’s fake
news literacy. This study helps address this gap. Results indicate that individuals’fake news
literacy increases when people more frequently use social media, gain more political
knowledge and become more confident in finding truth in politics –epistemic political
efficacy (Pingree, 2011;Pingree et al., 2012). In other words, individuals will be more likely to
discern what is fake news the more they navigate this social media information environment,
when they are more politically sophisticated, when they become more self-confident in
understanding and finding the truth in politics. This study helps to better showcase the
importance of contextualizing the role of political beliefs in the formation of fake news
literacy.
Previous research has found that fact-checking political information positively increased
individuals’epistemic political efficacy (York et al., 2020). People who constantly fact-check
news information are more likely to develop the sense and confidence in finding truth in
politics. Epistemic political efficacy was also found to increase information seeking behaviors
(Pingree, 2011). Specifically, when individuals have higher epistemic political efficacy, they
are more confident in their ability to find information, which in turn leads to additional news
Figure 1.
Interaction between
epistemic political
efficacy and social
media use on fake news
literacy
OIR
48,7
1480
consumption (Farman et al., 2018). This positive effect of epistemic political efficacy is
important as misinformation increasingly spreads across news media and social media.
While epistemic political efficacy is one of the desirable outcomes of fact-checking (Pingree
et al., 2012;York et al., 2020), research has not examined whether, and if so how, epistemic
political efficacy could contribute to fake news literacy. This study found that epistemic
political efficacy strongly helped in developing fake news literacy, defined as the degree of
familiarity and confidence people have in spotting fake news (Schmeichel et al., 2018). This
positive impact of epistemic political efficacy on fake news literacy was tested with several
multivariate regression strategies, including a more stringent causal autoregressive panel
data test. In all our different tests, epistemic political efficacy showed a positive and direct
fake news literacy predictive effect.
This study also finds that political knowledge is a positive and significant indicator of fake
news literacy development. When people are savvy about public affair issues and current
events, they also have the necessary tools to pinpoint false information and fake news. As a
type of media literacy, news literacy encapsulates the role of news production on democracy
and civic lives and has been found to increase skepticism in regard to misinformation
(Craft et al., 2016). Prior research suggested that news audiences need to have necessary
knowledge and skills regarding journalistic news practices to develop news literacy (Vraga
et al., 2021). The present study empirically found that link. An explanation is that individuals
who have higher levels of political knowledge also tend to consume news more thoroughly
and elaborate cognitively upon the news they consume, which in turn contributes to the
increasing fake news literacy. In addition, the lagged and autoregressive causal regression
models result showed that even in the long run, political knowledge still matters in building
fake news literacy over time. Perhaps signaling an over-the-time cognitive map and news
frames development that clearly helps people to identify fake news when exposed to it
(Shah et al., 2004), as more politically knowledgeable individuals become more thoughtful
news consumers who better understand political systems and political issues (Eveland, 2001;
Park and Kaye, 2019). Since the results show that increased political knowledge also
contributes to the development of fake news literacy, news socialization and a journalistic
education at early ages may contribute to bolster fake news literacy.
Likewise, this study found that social media contributes to cultivating fake news literacy
among users. As more fake news is circulating on social media, the more frequently
individuals use social media, the higher the chances to come across fake news. Allcott and
Gentzkow (2017) found that social media use directed users to fake news sites with more than
40% of fake news visitors arriving from social media. Relatedly, the more fake news
individuals encounter on social media, they are also more likely to develop higher levels of
fake news literacy, according to the cross-sectional regression model. This finding has a
practical implication for message design on social media since individuals can develop higher
fake news literacy when they find themselves exposed to more fake news. For example, the
more measures social media platforms adopt to flag fake news such as warning labels and
corrective messages, the more techniques and skills social media users may acquire to
identify fake news.
Surprisingly, overall news consumption on social media is not related to fake news literacy
in any of our models, cross-sectional, lagged regression and causal autoregressive regression.
One explanation for this may be that social media present mixed information with both
factual and misleading claims. The combination of both facts and misinformation may
confuse social media users and will not be sufficient for individuals to build systematic tools
to identify fake news and build up fake news literacy. While general social media use for
many other things beyond news, users may encounter fake news presented in different
contexts other than only news. Hence, the frequent exposure to different types of fake news
through general social media use can help users develop the skills to identify fake news.
Online
Information
Review
1481
In any case, future studies should help to better clarify this differential effect between
frequency of social media use, and social media use for news.
Also of importance, this study shows the direct effect of social media use on building fake
news literacy is contingent upon people’s epistemic political efficacy levels, lending support
for a moderation in the cross-sectional model. However, this moderation effect was not
significant in the lagged and autoregressive model. More specifically, for those who generally
use social media less often, high level of epistemic political efficacy helps them to better
identify fake news. The opposite is found for those who report low levels of epistemic political
efficacy when they use social media less often. For this group of the population, with low level
of epistemic political efficacy, using more frequently social media increases their chances of
developing fake news literacy. However, for the group of those with high level of epistemic
political efficacy, increased social media use decreases the development of fake news literacy.
In line with prior studies, where epistemic political efficacy was found to be a better predictor
of information seeking behaviors compared to internal and external political efficacy (Pingree
et al., 2012;Farman et al., 2018), results here indicate that people who are able to find the truth
in politics do not need further additional help from using social media more frequently to spot
fake news. They are already equipped with the necessary mechanisms to identify fake news
as they already try harder to systematically find objective facts in the news, and they are also
used to dig up objective facts in most political disputes. These news predispositions serve to
identify fake news on their own merit. Reversely, as people who have low levels of epistemic
political efficacy might turn away from seeking political information, the more they are
exposed to fake news in social media, the more they will familiarize and contrast between fake
and real news. Thus, for this group of people, overall social media use helps them.
An alternative explanation is that the more “low political efficacy”type of people use social
media for general purposes, the more they connect with others they trust in their networks,
which might also help them contextualize and clarify what kind of news they are exposed to,
fake, or verified factual information. Future research may clarify these connections as the
data gathered for this study did not allow for empirical testing based on content analytical
nuances.
While this study introduces a novel set of findings regarding fake news literacy, it also has
noteworthy limitations. First, the data rely, at least in part, on self-reporting. Assessing one’s
own ability to recognize fake news can present nuanced complexities for individuals as well.
For instance, individuals might lack of knowledge to identify fake news. In other words,
individuals might not know that they are exposed to fake news, and the self-reported news
literacy might differ from actual literacy. In addition, while the issue of fake news garnered
widespread attention since the 2016 US presidential elections (Allcott and Gentzkow, 2017;
Wardle, 2017), it wasn’t until the COVID-19 pandemic in 2020 that the general public became
overly familiar with the concepts of fake news and misinformation. Given that we collected
our data in 2019, some individuals could have less knowledge about fake news and
misinformation. Future research should try to capture the knowledge of individuals about
fake news to measure relevant literacy (see Huber et al., 2021). Second, this study explores the
role of the general social media use on fake news literacy development, and it does so after
controlling for specific social media use for news consumption. However, the measurement
instrument employed in the study relies on subjects’self-assessment, as opposed to
unobtrusive trace (big) digital data, which may not completely capture the nuances of
people’s social media news behaviors. Even though prior research has found that most self-
assessment reported data tends to positively correlate with digitally recorded trace data
(Haenschen, 2020), future research should also shed light on the way social media in general,
and social media news specifically are consumed.
The connection between social media use and fake news literacy may become increasingly
important, specially knowing that citizens rely on these social media platforms to socialize,
OIR
48,7
1482
get entertainment and consume political information (Shearer and Mitchell, 2021). Third, an
opt-in online panel survey was used to collect data, which might bring sampling and
measurement error. It is true that IPSOS XXX stratifies the sample based on a huge pool of
citizens, and the demographic breakdown largely resembles that of the general population.
Nevertheless, findings should be interpreted and the generalized with certain caution.
Complementary experimental studies may also contribute to better learning the ways in
which citizens become aware of misinformation in social media. For instance, initial efforts
along these lines have provided useful empirical evidence (Bastick, 2021).
What’s more, although our study may lack an international comparative perspective as is
based on a national representative sample from US, the findings can be cautiously generalized
to other countries which has similarlevels of democracy.For examples, some countries in global
south such as Thailand, Malaysia, Indonesia and Philippines are categorized as countries with
similarly imperfect democracy like US (Economist Intelligence Unit, 2021). Fake news literacy
plays an active role in informed citizenship and democracy and the factors impacting its
formation in the US might be similar to those factors in other countries that share similar levels
of democracy. In addition, many countries and the US share similar social media penetration
rate (Ruby, 2023), which makes our findings more applicable globally. Furthermore, although
the political contexts in other countries might be different, epistemic efficacy is an individual
characteristic that is found universally (Pingree, 2011;Pingree et al., 2012). Other types of
political efficacy such as internal political efficacy was found to be positively related to news
engagement across different counties (Lu and Luqiu, 2020). Therefore, the effects of epistemic
efficacy on fake news literacy could be similar across different countries.
Despite some limitations, this study sheds light on how the way people understand politics
and gain confidence in finding political truth may be key elements when confronting and
discerning fake news. People’s epistemic political efficacy fuels the process of fake news
literacy development especially in the context of social media. As social media use continues
to grow and shape how citizens navigate their social and political virtual lives, the results
showcased here underscore the importance of learning about the antecedents that explain
fake news literacy. If anything, with the help of these results, journalists, media outlets and
policymakers may be better positioned to provide citizens with efficient, preemptive and
corrective action mechanisms in the struggle against misinformation.
References
AAPOR (2011), “AAPOR American association for public opinion research (2011)”, Standard
Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys, available at:
http://aapor.org
Allcott, H. and Gentzkow, M. (2017), “Social media and fake news in the 2016 election”,Journal of
Economic Perspectives, Vol. 31 No. 2, pp. 211-236, doi: 10.1257/jep.31.2.211.
Amazeen, M.A. and Bucy, E.P. (2019), “Conferring resistance to digital disinformation: the inoculating
influence of procedural news knowledge”,Journal of Broadcasting and Electronic Media, Vol. 63
No. 3, pp. 15-432, doi: 10.1080/08838151.2019.1653101.
Astor, M. (2024), “Texas company was behind voter robocalls that impersonated biden, N.H. Says”,
available at: https://www.nytimes.com/2024/02/06/us/politics/biden-robocall-new-hampshire.html
Bastick, Z. (2021), “Would you notice if fake news changed your behavior? An experiment on the
unconscious effects of disinformation”,Computers in Human Behavior, Vol. 116, pp. 1-12,
doi: 10.1016/j.chb.2020.106633.
Boczkowski, P.J., Mitchelstein, E. and Matassi, M. (2018), “News comes across when I’m in a moment
of leisure: understanding the practices of incidental news consumption on social media”,New
Media and Society, Vol. 20 No. 10, pp. 3523-3539, doi: 10.1177/1461444817750396.
Online
Information
Review
1483
Borah, P. and Lorenzano, K.J. (2023), “Who corrects misinformation online? Self-perceived media
literacy and the moderating role of reflective judgment”,Online Information Review, doi: 10.
1108/oir-12-2022-0656.
Carpini, M.X.D. and Keeter, S. (1996), What Americans Know about Politics and Why it Matters, Yale
University Press, New Haven, CT.
Correa, T., Hinsley, A.W. and De Zuniga, H.G. (2010), “Who interacts on the Web?: the intersection of
users’personality and social media use”,Computers in Human Behavior, Vol. 26 No. 2,
pp. 247-253, doi: 10.1016/j.chb.2009.09.003.
Craig, S.C. and Maggiotto, M.A. (1982), “Measuring political efficacy”,Political Methodology, Vol. 8
No. 3, pp. 85-109.
Craft, S., Ashley, S. and Maksl, A. (2016), “Elements of news literacy: a focus group study of how
teenagers define news and why they consume it”,Electronic News, Vol. 10 No. 3, pp. 143-160,
doi: 10.1177/1931243116656716.
Denham, H. (2021), “ThesearetheplatformsthathavebannedTrumpandhisallies”,The Washington Post,
available at: https://www.washingtonpost.com/technology/2021/01/11/trump-banned-social-media/
Economist Intelligence Unit (2021), “Democracy index 2021: the China challenge”, available at: https://
www.eiu.com/n/campaigns/democracy-index-2021/
Eveland, W.P. Jr (2001), “The cognitive mediation model of learning from the news: evidence from
nonelection, off-year election, and presidential election contexts”,Communication Research,
Vol. 28 No. 5, pp. 571-601, doi: 10.1177/009365001028005001.
Farman, L., Riffe, D., Kifer, M. and Leder Elder, S. (2018), “Finding the truth in politics: an empirical
validation of the epistemic political efficacy concept”,Atlantic Journal of Communication,
Vol. 26 No. 1, pp. 1-15, doi: 10.1080/15456870.2018.1398162.
Ferrucci, P. and Hopp, T. (2023), “Let’s intervene: how platforms can combine media literacy and self-
efficacy to fight fake news”,Communication and the Public, Vol. 8 No. 4, pp. 367-389, doi: 10.
1177/20570473231203081.
First Draft News (2021), available at: https://firstdraftnews.org
Gil de Z
u~
niga, H., Diehl, T. and Ard
evol-Abreu, A. (2017), “Internal, external, and government political
efficacy: effects on news use, discussion, and political participation”,Journal of Broadcasting
and Electronic Media, Vol. 61 No. 3, pp. 574-596, doi: 10.1080/08838151.2017.1344672.
Gil de Z
u~
niga, H., Barnidge, M. and Diehl, T. (2018), “Political persuasion on social media: a moderated
moderation model of political discussion disagreement and civil reasoning”,The Information
Society, Vol. 34 No. 5, pp. 302-315, doi: 10.1080/01972243.2018.1497743.
Haenschen, K. (2020), “Self-reported versus digitally recorded: measuring political activity on
Facebook”,Social Science Computer Review, Vol. 38 No. 5, pp. 567-583, doi: 10.1177/
0894439318813586.
Hayes, A.F. (2017), Introduction to Mediation, Moderation, and Conditional Process Analysis:
A Regression-Based Approach, Guilford Press, New York, London.
Hinsley, A. and Holton, A.E. (2021), “Fake news cues: examining the impact of content, source, and
typology of news cues on people’s confidence in identifying mis- and disinformation”,
International Journal of Communication, Vol. 15, pp. 4984-5003.
Hopp, T. (2022), “Fake news self-efficacy, fake news identification, and content sharing on Facebook”,
Journal of Information Technology and Politics, Vol. 19 No. 2, pp. 229-252, doi: 10.1080/19331681.
2021.1962778.
Huber, B., Borah, P. and Gil de Z
u~
niga, H. (2021), “Taking corrective action when exposed to fake news:
the role of fake news literacy”,Journal of Media Literacy Education, Vol. 14 No. 2, pp. 1-14, doi: 10.
23860/jmle-2022-14-2-1, Pre-prints, available at: https://digitalcommons.uri.edu/jmle-preprints/23
Jamieson, K.H. and Waldman, P. (2003), The Press Effect: Politicians, Journalists, and the Stories that
Shape the Political World, Oxford University Press, New York, NY.
OIR
48,7
1484
Jun, Y., Meng, R. and Johar, G.V. (2017), “Perceived social presence reduces fact-checking”,Proceedings
of the National Academy of Sciences of the United States of America, Vol. 114 No. 23,
pp. 5976-5981, doi: 10.1073/pnas.1700175114.
Kim, Y., Hsu, S.H. and de Z
u~
niga, H.G. (2013), “Influence of social media use on discussion network
heterogeneity and civic engagement: the moderating role of personality traits”,Journal of
Communication, Vol. 63 No. 3, pp. 498-516, doi: 10.1111/jcom.12034.
Lee, S., Gil de Z
u~
niga, H. and Munger, K. (2023), “Antecedents and consequences of fake news
exposure: a two-panel study on how news use and different indicators of fake news exposure
affect media trust”,Human Communication Research, Vol. 49 No. 4, pp. 408-420, doi: 10.1093/
hcr/hqad019.
Lu, S. and Luqiu, L.R. (2020), “Does political efficacy equally predict news engagement across
countries? A multilevel analysis of the relationship among internal political efficacy, media
environment and news engagement”,New Media and Society, Vol. 22 No. 12, pp. 2146-2165,
doi: 10.1177/1461444819888417.
Lupia, A. and Philpot, T.S. (2005), “Views from inside the net: how websites affect young adults’
political interest”,The Journal of Politics, Vol. 67 No. 4, pp. 1122-1142, doi: 10.1111/j.1468-2508.
2005.00353.x.
Maksl, A., Ashley, S. and Craft, S. (2015), “Measuring news media literacy”,Journal of Media Literacy
Education, Vol. 6 No. 3, pp. 29-45, doi: 10.23860/jmle-6-3-3.
Maksl, A., Craft, S., Ashley, S. and Miller, D. (2017), “The usefulness of a news media literacy measure
in evaluating a news literacy curriculum”,Journalism and Mass Communication Educator,
Vol. 72 No. 2, pp. 228-241, doi: 10.1177/1077695816651970.
Maxwell, S.E., Cole, D.A. and Mitchell, M.A. (2011), “Bias in cross-sectional analyses of
longitudinal mediation: partial and complete mediation under an autoregressive model”,
Multivariate Behavioral Research, Vol. 46 No. 5, pp. 816-841, doi: 10.1080/00273171.2011.
606716.
McGregor, S. (2020), “Taking the temperature of the room: how political campaigns use social media to
understand and represent public opinion”,Public Opinion Quarterly, Vol. 84 No. 1, pp. 236-256,
doi: 10.1093/poq/nfaa012.
Molina, M.D., Sundar, S.S., Le, T. and Lee, D. (2021), “‘Fake news’is not simply false information: a
concept explication and taxonomy of online content”,American Behavioral Scientist, Vol. 65
No. 2, pp. 180-212, doi: 10.1177/0002764219878224.
Paisana, M., Pinto-Martinho, A. and Cardoso, G. (2020), “Trust and fake news: exploratory analysis of
the impact of news literacy on the relations with news content in Portugal”,Communication
and Society, Vol. 33 No. 2, pp. 105-117, doi: 10.15581/003.33.2.105-117.
Park, C.S. and Kaye, B.K. (2019), “Mediating roles of news curation and news elaboration in the
relationship between social media use for news and political knowledge”,Journal of
Broadcasting and Electronic Media, Vol. 63 No. 3, pp. 455-473, doi: 10.1080/08838151.2019.
1653070.
Pennycook,G.andRand,D.G.(2022),“Accuracy prompts are a replicable and generalizable
approach for reducing the spread of misinformation”,Nature Communications, Vol. 13 No. 1,
p. 2333, doi: 10.1038/s41467-022-30073-5.
Pew Research Center (2019), “Many Americans say made-up news is a critical problem that needs to
be fixed”, available at: https://www.journalism.org/wp-content/uploads/sites/8/2019/06/PJ_2019.
06.05_Misinformation_FINAL-1.pdf
Pingree, R.J. (2011), “Effects of unresolved factual disputes in the news on epistemic political efficacy”,
Journal of Communication, Vol. 61 No. 1, pp. 22-47, doi: 10.1111/j.1460-2466.2010.01525.x.
Pingree, R.J., Hill, M. and McLeod, D.M. (2012), “Distinguishing effects of game framing and
journalistic adjudication on cynicism and epistemic political efficacy”,Communication
Research, Vol. 40 No. 2, pp. 193-214, doi: 10.1177/0093650212439205.
Online
Information
Review
1485
Quintanilha, T., Torres da Silva, M. and Lapa, T. (2019), “Fake news and its impact on trust in the
news: using the Portuguese case to establish lines of differentiation”,Communication and
Society, Vol. 32 No. 1, pp. 17-33, doi: 10.15581/003.32.3.17-32.
Ruby, D. (2023), “Social media users —how many people use social media in 2023”, available at:
https://www.demandsage.com/social-media-users/
Schmeichel, M., Garrett, J., Ranschaert, R., Mcanulty, J., Thompson, S., Janis, S., Clark, C., Yagata, S.
and Bivens, B. (2018), “The complexity of learning to teach news media in social studies
education”,Journal of Media Literacy Education, Vol. 10 No. 2, pp. 86-103, doi: 10.23860/jmle-
2018-10-2-5.
Schwarzenegger, C. (2020), “Personal epistemologies of the media: selective criticality, pragmatic trust,
and competence–confidence in navigating media repertoires in the digital age”,New Media and
Society, Vol. 22 No. 2, pp. 361-377, doi: 10.1177/1461444819856919.
Shah, D.V., Kwak, N., Schmierbach, M. and Zubric, J. (2004), “The interplay of news frames on
cognitive complexity”,Human Communication Research, Vol. 30 No. 1, pp. 102-120, doi: 10.
1093/hcr/30.1.102.
Shearer, E. and Mitchell, A. (2021), “News use across social media platforms in 2020”, available at:
https://www.journalism.org/2021/01/12/news-use-across-social-media-platforms-in-2020/
Su, Y., Borah, P. and Xiao, X. (2022), “Understanding the ‘infodemic’: social media news use,
homogeneous online discussion, self-perceived media literacy and misperceptions about
COVID-19”,Online Information Review, Vol. 46 No. 7, pp. 1353-1372, doi: 10.1108/oir-06-
2021-0305.
Tandoc, E.C., Lim, Z.W. and Ling, R. (2017), “Defining ‘fake news’”,Digital Journalism, Vol. 6 No. 2,
pp. 137-153, doi: 10.1080/21670811.2017.1360143.
Tandoc, E.C., Lim, Z.W. and Ling, R. (2018a), “Defining “fake news:”A typology of scholarly
definitions”,Digital Journalism, Vol. 6 No. 2, pp. 137-153, doi: 10.1080/21670811.2017.
1360143.
Tandoc, E.C., Ling, R., Westlund, O., Duffy, A., Goh, D. and Lim, Z.W. (2018b), “Audiences’acts of
authentication in the age of fake news: a conceptual framework”,New Media and Society,
Vol. 20 No. 8, pp. 2745-2763, doi: 10.1177/1461444817731756.
Tewksbury, D., Weaver, A.J. and Maddex, B.D. (2001), “Accidently informed: incidental news
exposure on the world wide web”,Journalism and Mass Communication Quarterly, Vol. 78
No. 3, pp. 533-554, doi: 10.1177/107769900107800309.
Tully, M. and Vraga, E.K. (2018), “A mixed methods approach to examining the relationship between
news media literacy and political efficacy”,International Journal of Communication, Vol. 12,
pp. 766-787.
Tully, M., Madrid-Morales, D., Wasserman, H., Gondwe, G. and Ireri, K. (2022), “Who is responsible for
stopping the spread of misinformation? Examining audience perceptions of responsibilities and
responses in six Sub-Saharan African countries”,Digital Journalism, Vol. 10 No. 5, pp. 679-697,
doi: 10.1080/21670811.2021.1965491.
Valenzuela, S., Halpern, D., Katz, J.E. and Miranda, J.P. (2019), “The paradox of participation versus
misinformation: social media, political engagement, and the spread of misinformation”,Digital
Journalism, Vol. 7 No. 6, pp. 802-823, doi: 10.1080/21670811.2019.1623701.
Verba, S. and Nie, N.H. (1987), Participation in America: Political Democracy and Social Equality,
University of Chicago Press, Chicago, IL.
Vraga, E.K. and Tully, M. (2019), “News literacy, social media behaviors, and skepticism toward
information on social media”,Information, Communication and Society, Vol. 24 No. 2, pp. 1-17,
doi: 10.1080/1369118x.2019.1637445.
Vraga, E., Tully, M., Kotcher, J.E., Smithson, A.B. and Broeckelman-Post, M. (2015), “A multi-
dimensional approach to measuring news media literacy”,Journal of Media Literacy Education,
Vol. 7 No. 3, pp. 41-53, doi: 10.23860/jmle-7-3-4.
OIR
48,7
1486
Vraga, E., Bode, L. and Tully, M. (2020), “Creating news literacy messages to enhance expert
corrections of misinformation on Twitter”,Communication Research, Vol. 49 No. 2, pp. 1-23,
doi: 10.1177/0093650219898094.
Vraga, E.K., Tully, M., Maksl, A., Craft, S. and Ashley, S. (2021), “Theorizing news literacy behaviors”,
Communication Theory, Vol. 31 No. 1, pp. 1-21, doi: 10.1093/ct/qtaa005.
Wardle, C. (2017), “Fake new: it’s complicated”, available at: https://firstdraftnews.org/fake-news-
complicated/
Xiao, X. and Yang, W. (2023), “There’s more to news media skepticism: a path analysis examining
news media literacy, news media skepticism and misinformation behaviors”,Online
Information Review, Vol. 48 No. 3, pp. 441-456, doi: 10.1108/oir-04-2023-0172.
York,C.,Ponder,J.D.,Humphries,Z.,Goodall,C.,Beam,M.andWinters,C.(2020),“Effects of fact-checking
political misinformation on perceptual accuracy and epistemic political efficacy”,Journalism and
Mass Communication Quarterly, Vol. 97 No. 4, pp. 958-980, doi: 10.1177/1077699019890119.
Zhang, B., Inguanzo, I. and Gil de Z
u~
niga, H. (2022), “Examining the role of online uncivil discussion
and ideological extremity on illegal protest”,Media and Communication, Vol. 10 No. 4,
pp. 94-104, doi: 10.17645/mac.v10i4.5694.
Zimmer, B. (2020), “Infodemic: when unreliable information spreads far and wide”,The Wall Street
Journal, available at: https://www.wsj.com/articles/infodemic-when-unreliable-information-
spreads-far-and-wide-115834
About the authors
Bingbing Zhang is an assistant professor at the School of Journalism and Mass Communication from the
University of Iowa in the United States. She obtained her doctoral degree on Mass Communications from
Pennsylvania State University and a master’s degree on Mass Communications from Texas Tech
University and a master’s degree on Journalism and Communications from Jinan University in China.
Her research interests focus on political communication and media effects on individuals’political
beliefs, attitudes and behaviors. Bingbing Zhang is the corresponding author and can be contacted at:
bingbing-zhang@uiowa.edu
Avery E. Holton was appointed Chair of the Department of Communication at the University of Utah
in 2021 after previously serving as an Associate Chair. His research engages digital and social media,
news and information, and constructs of health, identity and ability. He serves as the University’s
Student Media Advisor and is an appointed Humanities Scholar, working with first-year students as
they transition into Humanities courses at the University. He also serves as a Research Co-Coordinator
for Utah’s Center for Excellence in Ethical, Legal, and Social Implications Research (UCEER), which is
currently funded by a $3.9m grant from the National Institutes of Health.
Homero Gil de Z
u~
niga holds a PhD in Politics at Universidad Europea de Madrid and a PhD in Mass
Communication at the University of Wisconsin–Madison, serves as Distinguished Research Professor at
the University of Salamanca where he directs the Democracy Research Unit (DRU), as Professor at
Pennsylvania State University, and as Senior Research Fellow at Universidad Diego Portales, Chile. His
research addresses the influence of new technologies and digital media over people’s daily lives, as well
as the effect of such use on the overall democratic process. He has published nearly a dozen books/
volumes and over 100 JCR peer-reviewed journal articles (i.e. Journal of Communication,Journal of
Computer-Mediated Communication,Political Communication,Human Communication Research,New
Media and Society,Communication Research, and many more).
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: permissions@emeraldinsight.com
Online
Information
Review
1487
