Amid the global discussion on ways to fight misinformation, journalists have been writing stories with graphical representations of data to expose misperceptions and provide readers with more accurate information. Employing an experimental design, this study explored to what extent news stories correcting misperceptions are effective in reducing them when the stories include data visualization and how influential readers’ prior beliefs, issue involvement and prior knowledge may be in that context. The study found that the presence of data visualization in news articles correcting misperceptions significantly enhanced the reduction of misperceptions among news readers with less than average prior knowledge about an issue. In addition, it was found that prior beliefs had a significant effect on news readers’ misperceptions regardless of the presence or absence of data visualization. In this way, this research offers some support for the notion that data visualization may be useful to decrease misperceptions under certain circumstances.
AikinKJBettsKRO’DonoghueAC, et al. (2015) Correction of overstatement and omission in direct-to-consumer prescription drug advertising. Journal of Communication65(4): 596–618.
2.
AlbaRRumbautRGMarotzK (2005) A distorted nation: Perceptions of racial/ethnic group sizes and attitudes toward immigrants and other minorities. Social Forces84(2): 901–919.
3.
AlesinaAMianoAStantchevaS (2018) Immigration and redistribution. Working Paper No. 24733, National Bureau of Economic Research, Cambridge, MA. DOI: 10.3386/w24733.
4.
BergerG (2018) Foreword. In: IretonCPosettiJ (eds) Journalism, ‘Fake News’ and Disinformation. Handbook for Journalism Education and Training. Paris: UNESCO, pp.7–13.
5.
BodeLVragaEK (2015) In related news, that was wrong: The correction of misinformation through related stories functionality in social media. Journal of Communication65: 619–638.
6.
BuhrmesterMKwangTGoslingSD (2011) Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality, data?Perspectives on Psychological Science6: 3–5.
7.
CohnD (2017) 5 key facts about US lawful immigrants. Pew Research Center, 8March.
8.
CookJLewandowskySEckerUKH (2017) Neutralizing misinformation through inoculation: Exposing misleading argumentation techniques reduces their influence. PLoS One12(5): e0175799.
9.
CookMP (2006) Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles. Science Education90(6): 1073–1091.
10.
Del VicarioMBessiAZolloF, et al. (2016) The spreading of misinformation online. Proceedings of the National Academy of Sciences of the United States of America113(3): 554–559.
11.
DixonGNMcKeeverBWHoltonAE, et al. (2015) The power of a picture: Overcoming scientific misinformation by communicating weight-of-evidence information with visual exemplars. Journal of Communication65(4): 639–659.
12.
EckerUKHLewandowskySFentonO, et al. (2014) Do people keep believing because they want to? Preexisting attitudes and the continued influence of misinformation. Memory and Cognition42: 292–304.
13.
EckerUKHLewandowskySSwireB, et al. (2011) Correcting false information in memory: Manipulating the strength of misinformation encoding and its retraction. Psychonomic Bulletin and Review18(3): 570–578.
FentimanLC (2017) When it comes to vaccines, rich parents get away with child neglect. The Washington Post, 10May.
16.
FestingerL (1957) A Theory of Cognitive Dissonance. Stanford, CA: Stanford University Press.
17.
GeidnerNPjesivacIImreI, et al. (2015) The role of interactive graphics in reducing misperceptions in the electorate. Visual Communication Quarterly22(3): 133–145.
18.
HallVBanerjeeEKenyonC, et al. (2017) Measles outbreak—Minnesota April–May 2017. MMWR. Morbidity and Mortality Weekly Report66: 713–717.
HayesAFMatthesJ (2009) Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods41(3): 924–936.
21.
HoffmanJ (2019) One more time, with big data: Measles vaccine doesn’t cause autism. The New York Times, 7March.
22.
HopkinsDJSidesJCitrinJ (2018) The muted consequences of correct information about immigration. The Journal of Politics81: 315–320.
23.
HviidAHansenJVFrischM, et al. (2019) Measles, mumps, rubella vaccination and autism: A nationwide cohort study. Annals of Internal Medicine170(8): 513.
24.
Institute of Medicine (2004) Immunization Safety Review: Vaccines and Autism. Washington, DC: National Academies Press (US). Available at: http://www.ncbi.nlm.nih.gov/books/NBK25344/ (accessed 20 April 2019).
IretonCPosettiJ (eds) (2018) Journalism, ‘Fake News’ and Disinformation. Handbook for Journalism Education and Training. Paris: UNESCO.
27.
KraftPWLodgeMTaberCS (2015) Why people “don’t trust the evidence” motivated reasoning and scientific beliefs. The Annals of the American Academy of Political and Social Science658(1): 121–133.
28.
KuklinskiJHQuirkPJJeritJ, et al. (2000) Misinformation and the currency of democratic citizenship. Journal of Politics62(3): 790–816.
29.
LeeE-JKimYW (2015) Effects of infographics on news elaboration, acquisition, and evaluation: Prior knowledge and issue involvement as moderators. New Media & Society18: 1579–1598.
30.
LewandowskySEckerUKHCookJ (2017) Beyond misinformation: Understanding and coping with the “post-truth” era. Journal of Applied Research in Memory and Cognition6(4): 353–369.
31.
LiaoQVFuW-T (2013) Beyond the filter bubble: Interactive effects of perceived threat and topic involvement on selective exposure to information. In: Proceedings of the SIGCHI conference on human factors in computing systems, Paris, France, 27 April–2 May, pp.2359–2368. New York, NY: ACM.
32.
MenaP (2020) Cleaning up social media: The effect of warning labels on likelihood of sharing false news on Facebook. Policy & Internet12(2): 165–183.
33.
NadeauRNiemiRGLevineJ (1993) Innumeracy about minority populations. Public Opinion Quarterly57(3): 332–347.
34.
NyhanBReiflerJ (2010) When corrections fail: The persistence of political misperceptions. Political Behavior32(2): 303–330.
35.
NyhanBReiflerJ (2018) The roles of information deficits and identity threat in the prevalence of misperceptions. Journal of Elections, Public Opinion and Parties29(2): 222–244.
36.
NyhanBReiflerJRicheyS, et al. (2014) Effective messages in vaccine promotion: A randomized trial. Pediatrics133(4): e835–e842.
37.
PandeyAVManivannanANovO, et al. (2014) The persuasive power of data visualization. IEEE Transactions on Visualization and Computer Graphics20(12): 2211–2220.
PasekJSoodGKrosnickJA (2015) Misinformed about the affordable care act? Leveraging certainty to assess the prevalence of misperceptions. Journal of Communication65(4): 660–673.
40.
PedersenAAttwellJHeveliD (2005) Prediction of negative attitudes toward Australian asylum seekers: False beliefs, nationalism, and self-esteem. Australian Journal of Psychology57(3): 148–160.
41.
PettyRECacioppoJT (1983) Central and peripheral routes to persuasion: Application to advertising. In: PercyLWoodsideA (eds) Advertising and Consumer Psychology. Lexington, MA: D.C. Heath and Company, pp.3–23.
42.
PettyRECacioppoJT (1986) The elaboration likelihood model of persuasion. In: BerkowitzL (ed.) Advances in Experimental Social Psychology, vol. 19. Orlando, FL: Academic Press, pp.123–205.
43.
PorterERussellK (2018) Migrants are on the rise around the world, and myths about them are shaping attitudes. The New York Times, 20June.
44.
PriceVCzilliEJ (1996) Modeling patterns of news recognition and recall. Journal of Communication46(2): 55–78.
45.
RedlawskDPCivettiniAJWEmmersonKM (2010) The affective tipping point: Do motivated reasoners ever “get it”?Political Psychology31: 563–593.
46.
SaundersKL (2017) The impact of elite frames and motivated reasoning on beliefs in a global warming conspiracy: The promise and limits of trust. Research and Politics4(3): 205316801771760.
47.
SidesJCitrinJ (2007) European opinion about immigration: The role of identities, interests and information. British Journal of Political Science37(3): 477–504.
48.
SunLH (2018) Percentage of young U.S. children who don’t receive any vaccines has quadrupled since 2001. The Washington Post, 11October.
49.
SundarSS (2008) The MAIN model: A heuristic approach to understanding technology effects on credibility. In: MetzgerMJFlanaginAJ (eds) Digital Media, Youth, and Credibility. Cambridge, MA: MIT Press, pp.73–100.
50.
TandocECLeeJCB (2020) When viruses and misinformation spread: How young Singaporeans navigated uncertainty in the early stages of the COVID-19 outbreak. New Media & Society0(0): 1–19.
51.
ThorsonE (2016) Belief echoes: The persistent effects of corrected misinformation. Political Communication33(3): 460–480.
52.
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.
53.
VragaEKBodeL (2017) Leveraging institutions, educators, and networks to correct misinformation: A commentary on Lewandosky, Ecker, and Cook. Journal of Applied Research in Memory and Cognition6(4): 382–388.
54.
WoodTPorterE (2019) The elusive backfire effect: Mass attitudes’ steadfast factual adherence. Political Behavior41(1): 135–163.
55.
YoungDGJamiesonKHPoulsenS, et al. (2017) Fact-checking effectiveness as a function of format and tone: Evaluating Factcheck.org and Flackcheck.org. Journalism and Mass Communication Quarterly95(1): 49–75.
