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The Harvard Kennedy School Misinformation Review1
September 2020, Volume 1, Special Issue on COVID-19 and Misinformation
Attribution 4.0 International (CC BY 4.0)
Reprints and permissions: misinforeview@hks.harvard.edu
DOI: https://doi.org/10.37016/mr-2020-39
Website: misinforeview.hks.harvard.edu
Research Article
Anger contributes to the spread of COVID-19 misinfor-
mation
A survey conducted over South Korean adults (N=513) reveals that emotions, specifically anger, contribute
to the broader spread of misinformation on COVID-19 by leading angry individuals to consider false claims
to be “scientifically credible.” This pattern is more evident among conservatives than liberals. Our finding
sheds light on new measures and journalistic interventions that could alleviate the public’s anger and fos-
ter science-based conversations during a public health crisis.
Authors: Jiyoung Han (1), Meeyoung Cha (2), Wonjae Lee (3)
Affiliations: (1) School of Computing, Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea, (2)
Data Science Group, Institute for Basic Science (IBS), Republic of Korea, (3) Graduate School of Culture Technology, Korea
Advanced Institute of Science and Technology (KAIST), Republic of Korea
How to cite: Han, J.; Cha, M.; Lee, W. (2020). Emotion and misinformation in times of public health crisis. The Harvard Ken-
nedy School (HKS) Misinformation Review, 1(3).
Received: June 8th, 2020. Accepted: August 28th, 2020. Published: September 17th, 2020.
Research questions
● What are the roles of negative emotions, such as anger and fear, in the spread of misinformation
about COVID-19?
● What is the cognitive mechanism that motivates people to share false claims about COVID-19?
● Are these roles of negative emotions on the spread of falsehoods different as a function of polit-
ical ideology?
Essay summary
● South Korea is among the first countries to hold a general election amid the COVID-19 pandemic.
Although emotional arousal during an election is nothing new (Marcus, Neuman, & McKuen
2000), this one is special. The imminent threat to the public health escalated fear and anger in
the Korean mass public (Kang, 2020); these negative emotions also likely fueled the broader and
faster spread of misinformation (Vosoughi, Roy, & Aral, 2018). This paper thus analyzes people's
beliefs toward misinformation in times of a public health crisis and explains the role of emotion
in diffusing false claims about COVID-19 in South Korea.
1A publication of the Shorenstein Center for Media, Politics, and Public Policy, at Harvard University, John F. Kennedy School
of Government.
Anger contributes to the spread of COVID-19 misinformation 2
● Prior research found that right-leaning individuals have a lower threshold for experiencing neg-
ative emotions than left-leaning individuals (Skitka, Bauman, Aramovich, & Morgan, 2006). Build-
ing on this literature, we investigate whether the impact of fear and anger during this “info-
demic” varies along ideological lines.
● We fielded an online survey with 513 South Korean adults in the run-up to the 2020 South Korean
legislative election (April 9th to 13th, 2020). Our findings confirm that those expressing a higher
level of anger were more likely to disseminate misinformation about COVID-19. Such individuals
considered the falsehoods, mainly about bogus cures, to be "scientifically credible."
● Moreover, this belief tendency was stronger among conservatives than liberals. The observed
effect was persistent after controlling for party identification, gender, age, region, education
level, and household income.
Implications
Anger fuels the COVID-19 misinformation
Studies have found profound behavioral differences associated with emotions: Fear is connected to “be-
havior reconsideration,” whereas anger to “strong action tendencies” (Groenendyk & Banks, 2014; Lerner
et al., 2003; Lerner & Keltner, 2001; Miller et al., 2009; Valentino et al., 2015; for a review, see Carver &
Harmon-Jones, 2009; Lerner & Keltner, 2000; Smith & Ellsworth, 1985).
Before acting on a claim, anxious individuals are prone to wait and search for information to verify
whether the claim is right or wrong (MacKuen et al., 2010; Turner et al., 2006; Valentino et al., 2008; see
de los Santos & Nabi, 2019; Zhao & Cai, 2009 for counter-evidence). To make accurate judgments, anxious
individuals tend to seek and learn related information with open minds.
On the other hand, angry individuals readily act on the given claim (including encouraging others to
join in) due to their propensity to resolve the undesired situation (Ilakkuvan et al., 2017; Kim, 2016; Lerner
& Tiedens, 2006; see Berger, 2011; Berger & Milkman, 2012 for counter-evidence). Compared to those
who are anxious, angry individuals are less likely to search for information; even if they do, they are in
favor of information that bolsters their beliefs and are against information that undermines their views
(MacKuen et al., 2010; Suhay & Erisen, 2018; Tiedens & Linton, 2001; Valentino et al., 2008; see de los
Santos & Nabi, 2019 for counter-evidence).
These findings are pertinent in explaining why, in our data, people who felt angry were more vulner-
able to misinformation and actively engaged in disseminating false claims about COVID-19. Anger mobi-
lizes and, in turn, angry individuals easily rationalize their act of sharing misinformation by deeming it
trustworthy. Actions without deliberation, however, could lead to detrimental consequences such as be-
lief in false cures, which distract people from urgent preventive measures like social distancing. Thus, we
argue that managing anger and better engaging the public in the science-based discussions are critical to
combat misinformation and minimize its potential harms.
Management of strong action tendencies associated with anger was helpful to South Korea’s fight against
COVID-19
Many analyses have applauded the South Korean government's transparency and openness in early test-
ing, rigorous contact tracing, and keeping the public informed during COVID-19, as these qualities effec-
tively reduce uncertainty, the primary cause of fear (Lerner & Keltner, 2000; Smith & Ellsworth, 1985)
associated with the new virus. Here, we are more attentive to how the government guidelines pertain to
public anger management.
Han; Cha; Lee 3
We focus on South Korea’s decision not to impose a lockdown, but instead to offer very detailed and
clear guidelines for communal safeguards, such as wearing a mask, washing hands, eating alone, and using
an elbow to cover a cough. The country also held a general election during the pandemic. Despite re-
strictions, such as having to wear a mask, having to keep a meter distance from others, and having to use
hand sanitizer and plastic gloves, the 66% voter turnout was the highest in 16 years. Given that angry
citizens have an urge to unleash their feelings (Groenendyk & Banks, 2014; Lerner & Tiedens, 2006;
Valentino et al., 2015), following these behavioral directions may elicit a sense of participation in a fight
against the pandemic, thus alleviating the public’s anger.
The lack of proper public anger management may, in part, explain why stringent measures on COVID-
19 (e.g., forceful lockdowns) backfire and lead to public protests. Cities around the world that have gone
into lockdown show an alarming rise of domestic violence incidents (Graham-Harrison et al., 2020). Frey
and colleagues (2020) found that across 111 countries, democratic governments’ more lenient ap-
proaches were about 20% more effective in reducing geographic mobility than autocratic governments’
stricter ones.
Such patterns are recursive in many social crises, whether economic recessions, natural disasters, or
disease outbreaks. Without an adequate release process, anger seldom disappears but transfers to other
domains. For example, Vasilopoulos and colleagues (2019) found that anger toward the 2015 Paris terror
attack contributed to the rise of far-right parties and policies treating immigrants as a national security
threat. Valentino, Wayne, and Oceno (2018) also reported that anger associated with threats to traditional
social norms and group hierarchies boosted ethnocentrism and sexism, whereas fear suppressed such
tendencies.
To prevent detrimental social behaviors fed by anger, it is crucial to preemptively redirect strong
action tendencies of the emotion into a positive direction by nurturing a sense of participation in a fight
against the disease. However, how effective such government interventions would be is subject to cultural
contexts. The success of South Korea might be rooted in its collectivist cultural traits, which are charac-
terized by conformity, group loyalty, and obedience towards authority (Frey, 2020). In individualistic cul-
tures, the mass public is more suspicious of government interventions.
Science-based conversation during the evolving public health crisis necessitates greater normative respon-
sibilities from partisan media and social media platforms
Despite their government’s rapid response to COVID-19, many South Koreans still experienced negative
emotions of fear and anger toward the outbreak (Kang, 2020). We found that anger, in particular, con-
tributes to a wider spread of misinformation about COVID-19. There was, however, an ideological differ-
ence. Our findings are more nuanced than prior research in that, in our study, conservatives did not report
a higher level of anger than their liberal counterparts (Skitka et al., 2006). Instead, angry conservatives
more frequently shared misinformation -- mostly on unverified precautionary measures and cures about
the new virus -- compared to angry liberals.
The present research is limited in accounting for the difference. Yet, our findings speak to the role of
partisan media in times of a public health crisis. Given that their audience is more likely to accept rumors
and act on misinformation, conservative media could take greater responsibility in fact-checking. Yet,
South Korean conservative media have received warnings from the Korea Communications Standards
Commission for releasing news stories riddled with errors about the COVID-19 crisis (Chae, 2020; Lee,
2020).
Relatedly, social media platforms' efforts to flag misinformation and prioritize reliable information
are critical. Facebook and Twitter have tweaked their algorithms to promote official accounts and they
have clamped down on malicious content about COVID-19. Although these efforts don’t completely avert
Anger contributes to the spread of COVID-19 misinformation 4
the spread of falsehoods online, research has shown that when a claim is fact-checked and found to be
false, its virality decreases (Friggeri et al., 2014).
Journalistic interventions, such as fact-checking and content moderation, are indispensable in fos-
tering science-based conversations about preventive measures and cures during the evolving public
health crisis. Because of a lack of validated therapeutics or a COVID-19 vaccine, the mitigation strategies
will continue to be heavily reliant on behavioral measures, such as personal hygiene, physical distancing,
and quarantines (Chinazzi et al., 2020). Since such measures require individuals to change their behaviors
according to validated information about the disease, we believe that effectively communicating the most
accurate information to the public is critical for minimizing the impact of the pandemic.
The present study used a South Korean sample, and thus its findings should not be overgeneralized
to other cultural contexts. However, research using American samples has documented similar patterns
of ideological differences: Audiences of conservative media outlets, such as Fox News and Rush Limbaugh,
were more prone to be misinformed and believe in conspiracy theories about the COVID-19 pandemic
(Hall & Albarrcin, 2020). This finding suggests that conservative individuals might be more vulnerable to
misinformation during the COVID-19 crisis, and thus engaged in a rhetoric of falsehoods, not necessarily
due to cultural reasons or the standing of the ruling or the opposition party. Individuals’ party identifica-
tion was included in our analyses as a covariate to rule out these potential confounding effects. Thus, we
anticipate that the current research contributes to the further theorization of ideological differences in
acceptance and dissemination of misinformation for a future pandemic.
Hypotheses
Emotion triggers an action (Frijda, 1986). Especially, high-arousal emotions, such as fear and anger, do so
more than low-arousal emotions such as sadness (Berger, 2011; Berger & Milkman, 2012). Given that
misinformation sharing requires action, and that fear and anger are the most prominent emotions during
the COVID-19 pandemic (Kang, 2020), we propose the following two hypotheses and examine how emo-
tion shapes the diffusion of falsehoods in times of the COVID-19 public health crisis.
Hypothesis 1: Individuals expressing anger are more likely to consider misinformation about COVID-
19 scientifically credible, and therefore share falsehoods with others more actively.
This relationship will vary along ideological lines.
Hypothesis 2: Individuals expressing fear are more likely to consider misinformation about COVID-
19 scientifically credible, and therefore share falsehoods with others more actively.
This relationship will vary along ideological lines.
Findings
Preliminary observations
Before the main analyses, we report descriptive statistics and correlations of the considered variables in
Table A in the Appendix. This preliminary examination reveals several noteworthy observations. First, an-
ger and fear—both negative and high arousal emotions—are highly correlated.2 This relationship is con-
2 r = .41, p < .001
Han; Cha; Lee 5
sistent with earlier findings (Vasilopoulos et al., 2019; Weeks, 2015). Second, political ideology is not as-
sociated with anger3 but with fear. In addition, conservatives experience a greater degree of fear4 than
liberals.5 Third, people living in the Daegu-Gyeongbuk area, which is the most severely impacted region
in the nation for COVID-19,6 and men,7 are more prone to be politically conservative than progressive.
Fourth, higher education makes people more critical towards misinformation,8 and reluctant to share it.9
Lastly, there is a strong positive relationship between beliefs in misinformation and the act of sharing
misinformation.10
Main analyses
Our hypotheses test whether anger (H1) and fear (H2) enhance misinformation sharing by making people
believe false claims about COIVD-19 and whether this indirect (or mediated) effect via beliefs in false
claims is moderated by political ideology. Figure 2 presents the hypothesized moderated-mediation. Ac-
cording to Muller, Judd, and Yzerbyt (2015), there are three preconditions for a moderated-mediation: (1)
no significant interaction effect between an independent variable (i.e., anger or fear) and a moderator
(i.e., political ideology) in predicting the dependent variable (i.e., misinformation sharing), (2) a significant
interaction effect between the independent variable and the moderator on a mediator (i.e., beliefs in false
claims), and (3) a significant main effect of the mediator on the dependent variable. We thus performed
a set of regression analyses. The full regression results are summarized in Table 1.
Finding 1: Participants expressing a higher level of anger toward COVID-19 estimated false claims about
the virus to be more scientifically credible, resulting in a higher degree of misinformation sharing. This
pattern was more evident among conservatives than liberals.
Looking at Model 1 in Table 1, the interaction between anger and ideology has no statistically significant
effect on misinformation sharing.11 The result indicates that regardless of participants being conservative
or liberal, anger has no direct relationship with misinformation sharing. In contrast, Model 2 in Table 1
shows a statistically significant interaction effect between anger and ideology on beliefs in false claims,12
as illustrated in Figure 1. Subsequently, Model 3 in Table 1 shows a positive relationship between beliefs
in false claims and misinformation sharing.13 These two results in concert suggest that conservatives, com-
pared to liberals, contribute more to the spread of misinformation about COVID-19, as they are more
likely to believe unverified claims.
3 r = –.06, p = .161
4 r = –.13, p = .003
5 We would, however, like to note the age effect, in that conservatives, in general, are older than liberals (r = –.21, p < .001).
6 r = –.10, p = .023
7 r = –.16, p < .001
8 r = –.14, p = .002
9 r = –.14, p = .002
10 r = .80, p < .001
11 b = –.11, SE = .07, p = .106
12 b = –.12, SE = .06, p = .036
13 b = .87, SE = .03, p < .001
Anger contributes to the spread of COVID-19 misinformation 6
Table 1. Regression results: The indirect effects of negative emotions and political ideology on misinfor-
mation sharing via beliefs in false claims about COVID-19 (N = 513)
Model 1
Model 2
Model 3
Misinformation
sharing
Beliefs in false
claims
Misinformation
sharing
b
SE
b
SE
b
SE
Constant
.71
1.47
1.14
1.30
.01
.93
Anger
.53
.28
.58*
.25
–.02
.18
Fear
.03
.33
–.02
.29
.02
.21
Ideology
(7 = extremely liberal)
.38
.31
.49
.27
–.03
.20
Anger × Ideology
–.11
.07
–.12*
.06
.01
.04
Fear × Ideology
.02
.08
.01
.07
.004
.05
Age
.02**
.01
.02**
.01
.002
.004
Region (1 = Daegu-Gyeongbuk)
–.26
.23
–.18
.20
–.24
.14
Education level
–.16**
.05
–.15**
.05
–.03
.03
Household income
.05
.03
.03
.03
.02
.02
Gender
(1 = women)
–.07
.21
–.17
.19
.08
.13
PartyID (4= strong supporters of MPK)
–.09
.07
–.18**
.06
–.01
.04
Beliefs in false claims
.87***
.03
R2
.065
.088
.629
* p < .05, **p < .01, *** p < .001.
Figure 1. The interaction effect of anger and political ideology on beliefs in false claims about COVID-19.
This cognitive mechanism behind misinformation sharing is presented in Figure 2. This indirect relation-
ship is further confirmed with a bootstrap re-sampling analysis.14 For the analyses, we used Hayes’ (2017)
PROCESSS macro and computed the 95% bias-corrected confidence intervals based on 10,000 samples.
14 indirect effect = –.11, bootSE = .04, 95% bias-corrected CI [–.1965 to –.0235]
Han; Cha; Lee 7
Figure 2. The indirect effect of anger and fear moderated by political ideology on misinformation sharing via beliefs in false
claims. Estimates are reported as unstandardized (standard error). Solid lines indicate significant regression coefficients at the
alpha level of .05. Dotted lines indicate insignificant regression coefficients.
Finding 2: Participants who expressed a higher level of fear toward COVID-19 did not necessarily consider
false claims about COVID-19 more scientifically credible than usual. No difference was found between con-
servatives and liberals. Accordingly, no indirect effect of fear and political ideology on misinformation shar-
ing was found via beliefs in false claims.
Looking at Model 1 in Table 1, the interaction between fear and ideology has no statistically significant
effect on misinformation sharing.15 The result indicates that regardless of participants being conservative
or liberal, fear has no direct influence on misinformation sharing. Next, Model 2 in Table 1 shows no sta-
tistically significant effect of fear on beliefs in false claims as a function of ideology.16 There is no ideolog-
ical difference in disseminating falsehoods. This insignificant indirect effect is graphed in Figure 2 and
confirmed with a bootstrap re-sampling analyses.17
Methods
Participants
We fielded a nationwide online survey in South Korea (N = 513) between April 9th and 13th. The Korea
Broadcasting System (KBS) Public Media Institute18 recruited study samples from an online panel of ap-
proximately 20,000 respondents. Consistent with the nation’s population statistics based on residence
15 b = .01, SE = .08, p = .845
16 b = .01, SE = .07, p = .845
17 indirect effect = .01, bootSE = .06, 95% bias-corrected CI [–.0973 to .1269]
18 See http://office.kbs.co.kr/bri/
Anger contributes to the spread of COVID-19 misinformation 8
registration in March 2020,19 our sample was matched to be the same proportions of individuals in terms
of key Korean demographics, including gender, age, and region. Given that Daegu-Gyeongbuk is South
Korea’s hardest-hit region from the COVID-19 pandemic, we purposefully recruited 30% of participants
from this area. From the sample selected, 50.3% were women, 36.6% resided in Seoul and Gyeonggi (i.e.,
the greater Seoul area), and 64.5% had some college education or higher. The average age was 47 years
(SD = 16.65) with a range of 18 to 94. The average household income was between ₩40,010,000 (about
$34,000) and ₩50,000,000 (about $42,000). The margin of error for total respondents was ±4.3%p at the
95% confidence level. The response rate was 8.92%.
Measures
Participants responded to the questions in the following order:
Emotions: We measured participants’ feelings about the COVID-19 outbreak. Using 6-point Likert scales
(1 = strongly disagree, 6 = strongly agree), participants indicated to what extent they agree or disagree
with the following statements presented in a random order: (1) I am angry, and (2) I am afraid.20
Beliefs in false claims: To assess participants’ beliefs in false claims about COVID-19, we identified twelve
false claims from a list of over 200 fact-checked rumors from China and South Korea. These COVID-19
rumors came from DXY.cn, a Chinese online community for physicians and health care professionals. This
site hosted a comprehensive list of rumors that were shared on Chinese social media. After removing
redundant content, any lockdown-related claims, or politically oriented content, we identified twelve
claims that also propagated in South Korea. All claims had been fact-checked and identified as false either
by the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC) in the US,
and/or the Korea Centers for Disease Control and Prevention (KCDC). The claims included:
• “Gargling with salt water can eliminate the virus”;
• “hair dryers can kill the virus”;
• “drinking hot water or hot tea can reduce the chances of getting infected with COVID-19”;
• “garlic can prevent infection”;
• “only certain age groups, races, or ethnicities are vulnerable to the virus”;
• “antibiotics or flu vaccines can prevent the disease”; and
• “you can test yourself for COVID-19 by holding your breath for 10 seconds” (see Table 2 for all
twelve claims).
Participants indicated whether they found each of the false claims “scientifically credible” or not with two
answer choices (0 = No, 1 = Yes). The items were presented in a random order. We computed the measure
of beliefs in false information by summing the “Yes” responses (Cronbach’s alpha = .70).
Misinformation sharing: Related to the twelve misinformation about COVID-19, participants were next
asked whether they would share each of the claims with others or not with two answer choices (0 = No,
19 See http://kosis.kr/eng/index/index.do
20 To measure anger, we used two-items (i.e., I am angry, and I am disgusted). So did for measuring anxiety (i.e., I am afraid, and
I am worried). However, given the low measurement reliabilities of anger (Spearman-Brown coefficient = .526) and anxiety (Spear-
man-Brown coefficient = .611), we used a single measure for each emotion.
Han; Cha; Lee 9
1 = Yes). The items were presented in a random order and summed to create the measure of misinfor-
mation sharing (Cronbach’s alpha = .77).
Political ideology: Participants indicated their political ideology on a 7-point scale (1 = extremely conserva-
tive, 4 = moderate, 7 = extremely liberal).
Party identification: Party identification was assessed using a standard branching measure. Participants
first indicated which party they supported by selecting one answer from a list of political parties in South
Korea. Those identifying themselves as supporters of the Minjoo Party of Korea (MPK, the progressive
ruling party) and the United Future Party (UFP, the conservative, opposing party) were then asked to in-
dicate to what extent they supported their parties on a 3-point scale (1 = somewhat support, 3= strongly
support). Those identifying themselves as independents or supporters of some other party were asked
whether they think of themselves as closer to supporters of MPK, supporters of UFP, or neither. For anal-
yses, these measures were recoded into a single measure ranging from –4 (strong supporters of UFP) to
+4 (strong supporters of MPK). Pure independents were coded as 0; UFP-leaners were coded as –1 and
MPK-leaners were coded as +1.
Gender: Participants indicated their gender with two answer choices (0 = men, 1 = women).
Age. Participants were asked to write down their age.
Region: Participants indicated their residence area with multiple choices of (1) Seoul, (2) Busan, (3) Daegu,
(4) Incheon, (5) Gwangju, (6) Daejeon, (7) Ulsan, (8) Gyeonggi, (9) Gangwon, (10) Chungbuk, (11) Chung-
nam, (12) Jeonbuk, (13) Jeonnam, (14) Gyeongbuk, (15) Gyeongnam, (16) Jeju, and (17) Sejong. For our
analyses, the responses were recoded as 1 (Daegu-Gyeongbuk, COVID-19 hotspots in South Korea) and 0
(the other areas).
Education level: Participants indicated their level of education with multiple choices of (1) No elementary
school diploma, (2) Elementary school graduates, (3) No middle school diploma, (4) Middle school gradu-
ates, (5) No high school diploma, (6) High school graduates, (7) Some college, (8) Professional college
degrees, (9) 4-year university students, (10) Bachelor’s degrees, (11) Graduate students, and (12) Master’s
degrees or higher.
Household income: Participants indicated their household income with multiple choices of (1) Less than
₩10,000,000, (2) Between ₩10,010,000 and ₩20,000,000, (3) Between ₩20,010,000 and ₩30,000,000,
(4) Between ₩30,010,000 and ₩40,000,000, (5) Between ₩40,010,000 and ₩50,000,000, (6) Between
₩50,010,000 and ₩60,000,000, (7) Between ₩60,010,000 and ₩70,000,000, (8) Between ₩70,010,000
and ₩80,000,000, (9) Between ₩80,010,000 and ₩90,000,000, (10) Between ₩90,010,000 and
₩100,000,000, and (11) More than ₩100,000,000.
Anger contributes to the spread of COVID-19 misinformation 10
Table 2. Twelve false claims about COVID-19 (N = 513)
Beliefs in false
claims
Misinformation
sharing
Even if completely cured, COVID-19 patients suffer from
life-long lung damage.
63.7%
53.1%
A runny nose is a symptom of cold, not COVID-19.
31.6%
25.3%
Hair dryers can kill the virus.
6.2%
7.6%
Drinking alcohol can kill the virus.
2.6%
3.7%
Only certain age groups, races, or ethnicities are vulnerable
to the virus.
68.0%
56.2%
Antibiotics or flu vaccines can prevent the disease.
27.2%
22.3%
You can test yourself for COVID-19 by holding your breath
for 10 seconds.
8.7%
9.4%
Garlic can prevent infection.
19.9%
17.5%
Gargling with salt water can eliminate the virus.
7.3%
7.7%
The virus can penetrate into the body through contact.
19.0%
15.7%
Smoking can kill the virus.
4.2%
2.4%
Drinking hot water or hot tea can reduce the chances of
getting infected with COVID-19.
32.6%
31.1%
Note: Results are the percentage of “Yes” responses to the questions of “Beliefs in false claims” and “Mis-
information sharing.”
Han; Cha; Lee 11
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Acknowledgement
We thank Richard Moore for his feedback on this article.
Funding
This work was partly supported by a research grant for new scholars from the Korean Society for Journal-
ism and Communication Studies (KSJCS) and the Korean Broadcasting System (KBS) in 2020. J. Han was
supported by the National Research Foundation of Korea (NRF-2020S1A5B5A16083698). M. Cha was sup-
ported by the Institute for Basic Science (IBS-R029-C2). W. Lee was supported by the National Research
Foundation of Korea (NRF-2016S1A3A2925033).
Competing interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or
publication of this article.
Ethics
The institutional review board at KAIST approved the research protocol. Human subjects gave informed
consent before participating and were debriefed at the end of the study.
Copyright
This is an open access article distributed under the terms of the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided that the original
author and source are properly credited.
Data availability
All materials needed to replicate this study are available via the Harvard Dataverse:
https://doi.org/10.7910/DVN/TIN0SK.
Han; Cha; Lee 15
Appendix
Table A. Descriptive statistics and intercorrelations (N = 513)
Range
Descriptive
statistics
Correlations
M
SD
1
2
3
4
5
6
7
8
9
10
1. Ideology
1 to 7
4.18
1.17
—
2. Anger
1 to 6
3.91
1.42
–.06
—
3. Fear
1 to 6
3.92
1.31
–.13**
.41***
—
4. Beliefs in false claims
0 to 12
2.91
2.07
–.08
.10*
.11*
—
5. Misinformation sharing
0 to 12
2.52
2.30
–.07
.10*
.10*
.80***
—
6. Age
18 to 94
47.47
15.65
–.21***
.06
.13**
.17***
.15**
—
7. Region (1 = Daegu-Gyeongbuk)
0 to 1
.27
.44
–.10*
.04
.07
.001
–.03
.02
—
8. Education level
2 to 12
9.08
2.05
.03
–.04
–.01
–.14**
–.14**
–.10*
–.08
—
9. Household income
1 to 12
5.32
3.09
.05
–.06
–.08
–.004
.01
–.18***
.01
.17***
—
10. Gender (1 = women)
0 to 1
.50
.50
–.16***
–.14***
–.11**
–.08
–.05
.01
.004
.17***
–.05
—
11. Party identification
–4 to 4
.58
2.06
.65***
–.12*
–.22***
–.14**
–.11*
–.23***
–.06
.01
.05
–.08
* p < .05, **p < .01, *** p < .001.
