With the rise of digital media, conspiracy theories infamous for their emotional manipulation have challenged science epistemology and democratic discourse. Despite extensive literature on misinformation and the role of emotion in persuasion, less is understood about how emotion is used in conspiracy and debunking messages on video platforms and the impact of emotional framing on public engagement with science on social media. Our article fills this gap by analyzing thousands of YouTube videos that propagate or debunk COVID-19 conspiracy theories from March to May 2020. We found that conspiracy and debunking videos used the emotions of trust and fear differently depending on the issue framing of the conspiracy. Our article also reveals a dilemma facing debunking messages—when debunking videos used more trust-related emotions, these videos received more likes yet fewer views. These findings shed new light on the role of emotion on user engagement with misinformation and its correction on digital platforms.
AhmedWVidal-AlaballJDowningJ, et al. (2020) COVID-19 and the 5G conspiracy theory: social network analysis of Twitter data. Journal of Medical Internet Research22(5), e19458.
2.
AmarasekaraIGrantWJ (2018) Exploring the YouTube science communication gender gap: a sentiment analysis. Public Understanding of Science28(1): 68–84.
3.
AndreottaMNugrohoRHurlstoneMJ, et al. (2019) Analyzing social media data: a mixed-methods framework combining computational and qualitative text analysis. Behavior Research Methods51(4): 1766–1781.
BaleJM (2007) Political paranoia v. political realism: on distinguishing between bogus conspiracy theories and genuine conspiratorial politics. Patterns of Prejudice41(1): 45–60.
6.
BarrettLFMesquitaBOchsnerKN, et al. (2007) The experience of emotion. Annual Review of Psychology58: 373–403.
BilandzicHKinnebrockSKlinglerM (2020) The emotional effects of science narratives: a theoretical framework. Media and Communication8(1): 151–163.
9.
BodeLVragaEK (2017) See something, say something: correction of global health misinformation on social media. Health Communication33(9): 1–10.
10.
BraderT (2006) Campaigning for Hearts and Minds: How Emotional Appeals in Political Ads Work. Chicago, IL: The University of Chicago Press.
11.
BurgessJGreenJ (2018) Youtube: Online Video and Participatory Culture. Hoboken, NJ: John Wiley & Sons.
12.
ChadwickAVaccariC (2019) News sharing on UK social media: misinformation, disinformation, and correction. Report, Online Civic Culture Centre, Loughborough University, Loughborough.
13.
ChenKChenAZhangJ, et al. (2020) Conspiracy and debunking narratives about COVID-19 origins on Chinese social media: how it started and who is to blame. Harvard Kennedy School Misinformation Review1: 1–31.
14.
ChenKKimSJGaoQ, et al. (2022) Visual framing of science conspiracy videos: integrating machine learning with communication theories to study the use of color and brightness. Computational Communication Research4(1): 98–134.
15.
ChoiJLeeSYJiSW (2021) Engagement in emotional news on social media: intensity and type of emotions. Journalism & Mass Communication Quarterly: 1017–1040.
16.
CichockaA (2020) To counter conspiracy theories, boost well-being. Nature587(7833): 177.
FerraraE (2020, June2) What types of COVID-19 conspiracies are populated by Twitter bots? Available at: https://arxiv.org/abs/2004.09531 (accessed 22 August 2020).
21.
FongARoozenbeekJGoldwertD, et al. (2021) The language of conspiracy: a psychological analysis of speech used by conspiracy theorists and their followers on Twitter. Group Processes & Intergroup Relations24(4): 606–623.
22.
FreelonD (2014) On the interpretation of digital trace data in communication and social computing research. Journal of Broadcasting & Electronic Media58(1): 59–75.
23.
FreilingIKrauseNMScheufeleDA, et al. (2021) Believing and sharing misinformation, fact-checks, and accurate information on social media: the role of anxiety during COVID-19. New Media & Society. Epub ahead of print 22 April. DOI: 10.1177/14614448211011451.
24.
GerbaudoPMarognaFAlzettaC (2019) When “positive posting” attracts voters: user engagement and emotions in the 2017 UK election campaign on Facebook. Social Media + Society5(4): 1–11.
25.
GermaniFBiller- AndornoN (2021) The anti-vaccination infodemic on social media: a behavioral analysis. PLoS ONE16(3): e0247642.
26.
GertsDShelleyCDParikhN, et al. (2021) “Thought I’d share first” and other conspiracy theory tweets from the COVID-19 infodemic: exploratory study. JMIR Public Health and Surveillance7(4): e26527.
27.
GoffmanE (1974) Frame Analysis: An Essay on the Organization of Experience. Cambridge, MA: Harvard University Press.
28.
JolleyDPatersonJL (2020) Pylons ablaze: examining the role of 5G COVID-19 conspiracy beliefs and support for violence. British Journal of Social Psychology59(3): 628–640.
29.
JungAKRossBStieglitzS (2020) Caution: rumors ahead—a case study on the debunking of false information on Twitter. Big Data & Society7(2): 1–15.
30.
KatzJEMaysKK (2019) Journalism and Truth in an Age of Social Media. Oxford: Oxford University Press.
31.
KhanML (2017) Social media engagement: what motivates user participation and consumption on YouTube?Computers in Human Behavior66: 236–247.
32.
KimSJVillanuevaIChenK (2022) Going beyond affective polarization: how emotions and identities are used in anti-vaccination TikTok videos. Under Review.
33.
KrauseNMFreilingIBeetsB, et al. (2020) Fact-checking as risk communication: the multi-layered risk of misinformation in times of COVID-19. Journal of Risk Research 23(7–8): 1052–1059.
34.
KruseLMNorrisDRFlinchumJR (2018) Social media as a public sphere? Politics on social media. The Sociological Quarterly59(1): 62–84.
35.
LangADhillonKDongQ (1995) The effects of emotional arousal and valence on television viewers’ cognitive capacity and memory. Journal of Broadcasting & Electronic Media39(3): 313–327.
36.
LangANewhagenJReevesB (1996) Negative video as structure: emotion, attention, capacity, and memory. Journal of Broadcasting & Electronic Media40(4): 460–477.
37.
LeeCS (2019) Web series, YouTube, and politics: affective and emotional dimensions of wigs lauren’s user comments. Social Media + Society5(1): 1–12.
38.
LewandowskySEckerUKSeifertCM, et al. (2012) Misinformation and its correction: continued influence and successful debiasing. Psychological Science in the Public Interest13(3): 106–131.
39.
MacKuenMMarcusGNeumanWR, et al. (2010) Affective intelligence or personality? State vs. trait influences on citizens’ use of political information. State vs. trait influences on citizens’ use of political information. In: APSA 2010 annual meeting paper, 2–5September, Washington, DC.
40.
MacKuenMMillerPRMarcusG, et al. (2011) The attentive citizen: the dynamic impact of emotions on attention to political news over time. In: APSA 2011 annual meeting paper, September 1–4, Seattle, WA.
41.
MaratosFA (2011) Temporal processing of emotional stimuli: the capture and release of attention by angry faces. Emotion11(5): 1242–1247.
42.
MarcellinoWToddCHelmesJK, et al. (2021) Detecting conspiracy theories on social media improving machine learning to detect and understand online conspiracy theories. Report no. RR-A676-1, 2021. May. Santa Monica, CA: Rand Corporation.
43.
MarchalNAuH (2020) “Coronavirus explained”: YouTube, COVID-19, and the socio-technical mediation of expertise. Social Media + Society6(3): 1–4.
44.
MarcusGENeumanWRMacKuenM (2000) Affective Intelligence and Political Judgment. Chicago, IL: The University of Chicago Press.
NabiRL (2003) Exploring the framing effects of emotion: do discrete emotions differentially influence information accessibility, information seeking, and policy preference?Communication Research30(2): 224–247.
47.
NabiRL (2010) The case for emphasizing discrete emotions in communication research. Communication Monographs77(2): 153–159.
48.
NabiRL (2015) Emotional flow in persuasive health messages. Health Communication30(2): 114–124.
49.
NiehausIJonssonG (2005) Dr. Wouter Basson, Americans, and wild beasts: men’s conspiracy theories of HIV/AIDS in the South African Lowveld. Medical Anthropology24(2): 179–208.
50.
OliverJEWoodTJ (2014) Conspiracy theories and the paranoid style(s) of mass opinion. American Journal of Political Science58(4): 952–966.
51.
OswaldS (2016) Conspiracy and bias: argumentative features and persuasiveness of conspiracy theories. In:11th international conference of the ontario society for the study of argumentation (OSSA), Windsor, ON, Canada, 18–21May, pp. 1–16, Ontario Society of the Study of Argumentation. https://scholar.uwindsor.ca/ossaarchive/OSSA11/papersandcommentaries/168/
52.
PalAChuaAYKGohDHL (2020) How do users respond to online rumor rebuttals?Computers in Human Behavior106: 1–11.
53.
PanchenkoA (2016) Introduction: anthropology and conspiracy theory. Forum for Anthropology and Culture12: 157–160.
54.
PapacharissiZ (2002) The presentation of self in virtual life: characteristics of personal home Pages. Journalism & Mass Communication Quarterly79(3): 643–660.
55.
PasquettoISwire-ThompsonBAmazeenMA, et al. (2020) Tackling misinformation: what researchers could do with social media data. Harvard Kennedy School (HKS) Misinformation Review1(8): 1–14.
56.
PennycookGMcPhetresJZhangY, et al. (2020) Fighting COVID-19 misinformation on social media: experimental evidence for a scalable accuracy-nudge intervention. Psychological Science31(7): 770–780.
RosenbuschHEvansAZeelenbergM (2019) Multilevel emotion transfer on YouTube: disentangling the effects of emotional contagion and homophily on video audiences. Social Psychological and Personality Science10(8): 1028–1035.
59.
SangalangAOphirYCappellaJN (2019) The potential for narrative correctives to combat misinformation. Journal of Communication69(3): 298–319.
60.
SchererKR (2005) What are emotions? And how can they be measured?Social Science Information44(4): 695–729.
61.
ScheufeleDAKrauseNM (2019) Science audiences, misinformation, and fake news. Proceedings of the National Academy of Sciences116(16): 7662–7669.
62.
SchmittJBRiegerDRutkowskiO, et al. (2018) Counter-messages as prevention or promotion of extremism?! The potential role of YouTube. Journal of Communication68(4): 780–808.
TingleyDWagnerG (2017) Solar geoengineering and the chemtrails conspiracy on social media. Palgrave Communications3(1): 1–7.
65.
TrevorsGKendeouP (2020) The effects of positive and negative emotional text content on knowledge revision. Quarterly Journal of Experimental Psychology73(9): 1326–1339.
66.
TufekciZ (2018) YouTube, the great radicalizer. The New York Times, 18March, p. 10.
67.
TullyMBodeLVragaEK (2020) Mobilizing users: does exposure to misinformation and its correction affect users’ responses to a health misinformation post?Social Media + Society6(4): 1–12.
68.
van der MeerTGJinY (2020) Seeking formula for misinformation treatment in public health crises: the effects of corrective information type and source. Health Communication35(5): 560–575.
69.
van ProoijenJ-W (2018) The Psychology of Conspiracy Theories. Abingdon: Routledge.
70.
van ProoijenJ-WDouglasKM (2018) Belief in conspiracy theories: basic principles of an emerging research domain. European Journal of Social Psychology48(7): 897–908.
71.
van ProoijenJ-WLigthartJRosemaS, et al. (2022) The entertainment value of conspiracy theories. The British Psychological Society113: 25–48.
72.
VosoughiSRoyDAralS (2018) The spread of true and false news online. Science359(6380): 1146–1151.
73.
WangWHuangY (2021) Countering the “harmless e-cigarette” myth: the interplay of message format, message sidedness, and prior experience with e-cigarette use in misinformation correction. Science Communication43(2): 170–198.
74.
WebsterJG (2014) The Marketplace of Attention: How Audiences Take Shape in a Digital Age. Cambridge, MA: MIT Press.
YuJ (2014) We look for social, not promotion: brand post strategy, consumer emotions, and engagement. International Journal of Media & Communication1(2): 28–37.
77.
ZhangYWangLZhuJJH, et al. (2021) Conspiracy vs science: a large-scale analysis of online discussion cascades. World Wide Web24: 585–606.
78.
ZolloFNovakPKDel VicarioM, et al. (2015) Emotional dynamics in the age of misinformation. PLoS ONE10(9): e0138740.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
