Restricted accessResearch articleFirst published online 2025-3
The higher the news literacy,the wider the partisan gap on misinformation acceptance? The three-way interaction effects of news literacy,partisanship,and exposure to partisan YouTube channels on misinformation acceptance
Drawing on two competing hypotheses from the prevention and partisan gap frameworks, this study tests how news literacy, partisanship, and exposure to partisan YouTube channels interact to influence misinformation acceptance. Partisan YouTube channels in this study refer to a type of soft journalistic content with a partisan perspective. Panel survey data (N = 808) collected during the 2020 South Korean General Election campaign were analyzed. Supporting the partisan gap hypothesis, the results show that when exposed to partisan YouTube channels, those with higher news literacy were more likely to process misinformation in a biased manner, such that party-congenial misinformation is more likely to be accepted, while party-uncongenial misinformation is more likely to be rejected with an increase in news literacy level. This indicates that the effects of news literacy on misinformation acceptance vary depending on political factors. Furthermore, in the context of politically biased media, the partisan gap widens among those with greater news literacy.
ChristWGPotterWJ (1998) Media literacy, media education, and the academy. Journal of Communication48: 5–15.
2.
ChungMJones-JangSM (2022) Red media, blue media, Trump briefings, and COVID-19: examining how information sources predict risk preventive behaviors via threat and efficacy. Health Communication37: 1707–1714.
3.
ColleoniERozzaAArvidssonA (2014) Echo chamber or public sphere? Predicting political orientation and measuring political homophily in Twitter using big data. Journal of Communication64: 317–332.
4.
CraftSAshleySMakslA (2017) News media literacy and conspiracy theory endorsement. Communication and the Public2: 388–401.
5.
FlemingJ (2014) Media literacy, news literacy, or news appreciation? A case study of the news literacy program at Stony Brook University. Journalism & Mass Communication Educator69: 146–165.
6.
FlynnDJNyhanBReiflerJ (2017) The nature and origins of misperceptions: understanding false and unsupported beliefs about politics. Political Psychology38: 127–150.
7.
GarrettRKLongJAJeongMS (2019) From partisan media to misperception: affective polarization as mediator. Journal of Communication69: 490–512.
8.
GrahamJWOlchowskiAEGilreathTD (2007) How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prevention Science8: 206–213.
9.
HamMLeeSW (2020) 유튜브 정보 규제에 대한 이용자들의 인식 연구 [A study on users’ perceptions of regulations on information distributed on YouTube]. The Journal of the Korea Contents Association20: 36–50.
10.
HameleersMVan der MeerTGLA (2020) Misinformation and polarization in a high-choice media environment: how effective are political fact-checkers?Communication Research47: 227–250.
11.
HobbsRFrostR (2003) Measuring the acquisition of media-literacy skills. Reading Research Quarterly38: 330–355.
12.
Jones-JangSMMortensenTLiuJ (2021) Does media literacy help identification of fake news? Information literacy helps, but other literacies don’t. American Behavioral Scientist65: 371–388.
13.
KahanD (2010) Fixing the communications failure. Nature463: 296–297.
14.
KahanDM (2012) Ideology, motivated reasoning, and cognitive reflection: an experimental study. Judgment and Decision Making8: 407–424.
15.
KahanDMPetersEWittlinM, et al. (2012) The polarizing impact of science literacy and numeracy on perceived climate change risks. Nature Climate Change2: 732–735.
16.
KahneJBowyerB (2017) Educating for democracy in a partisan age: confronting the challenges of motivated reasoning and misinformation. American Educational Research Journal54: 3–34.
17.
KimCMinY (2021) 2020년 총선과 x유튜브 저zz널리즘: 방송사 채널과 인플루언서 채널 선거 동영상의 공정성과 품질 분석 [The 2020 parliamentary election and YouTube journalism: an analysis of the fairness and quality of election videos on the YouTube channels of major broadcasters and political influencers]. Broadcasting & Communication22: 130–166.
18.
Knobloch-WesterwickSWesterwickA (2023) Algorithmic personalization of source cues in the filter bubble: self-esteem and self-construal impact information exposure. New Media & Society25: 2095–2117.
19.
KuKYLKongQSongY, et al. (2019) What predicts adolescents’ critical thinking about real-life news? The roles of social media news consumption and news media literacy. Thinking Skills and Creativity33: 100570.
20.
KundaZ (1990) The case for motivated reasoning. Psychological Bulletin108: 480–498.
21.
MartensHHobbsR (2015) How media literacy supports civic engagement in a digital age. Atlantic Journal of Communication23: 120–137.
22.
MihailidisP (2009) Beyond cynicism: media education and civic learning outcomes in the university. International Journal of Learning and Media1: 19–31.
23.
MihailidisP (2012) News Literacy: Global Perspectives for the Newsroom and the Classroom. Bern: Peter Lang.
24.
MihailidisPViottyS (2017) Spreadable spectacle in digital culture: civic expression, fake news, and the role of media literacies in “post-fact” society. American Behavioral Scientist61: 441–454.
25.
MillerJMSaundersKLFarhartCE (2016) Conspiracy endorsement as motivated reasoning: the moderating roles of political knowledge and trust. American Journal of Political Science60: 824–844.
NyhanBReiflerJ (2010) When corrections fail: the persistence of political misperceptions. Political Behavior32: 303–330.
31.
OttoLGloggerIBoukesM (2017) The softening of journalistic political communication: a comprehensive framework model of sensationalism, soft news, infotainment, and tabloidization. Communication Theory27: 136–155.
32.
ParkYMChaeJHKimSK, et al. (2021) The effects of media literacy education and its influence on digital citizenship: focusing on CMF education programs in Korea. The Journal of Information Systems30: 113–135.
33.
PetersonEIyengarS (2021) Partisan gaps in political information and information-seeking behavior: motivated reasoning or cheerleading?American Journal of Political Science65: 133–147.
PotterWJ (2004) Argument for the need for a cognitive theory of media literacy. American Behavioral Scientist48: 266–272.
36.
PotterWJ (2010) The state of media literacy. Journal of Broadcasting & Electronic Media54: 675–696.
37.
RubinDB (1987) Multiple Imputation for Nonresponse in Surveys. New York: John Wiley & Sons.
38.
SmithGSearlesK (2014) Who let the (attack) dogs out? New evidence for partisan media effects. Public Opinion Quarterly78: 71–99.
39.
TaberCSLodgeM (2006) Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science50: 755–769.
40.
TaberCSCannDKucsovaS (2009) The motivated processing of political arguments. Political Behavior31: 137–155.
41.
TullyMVragaEKBodeL (2020) Designing and testing news literacy messages for social media. Mass Communication and Society23: 22–46.
42.
Van BuurenS (2018) Flexible Imputation of Missing Data. Boca Raton, FL: CRC press.
43.
Van der LindenSPanagopoulosCRoozenbeekJ (2020) You are fake news: political bias in perceptions of fake news. Media, Culture & Society42: 460–470.
44.
Von HippelPT (2009) How to impute interactions, squares, and other transformed variables. Sociological Methodology39: 265–291.
45.
Vonbun-FeldbauerRMatthesJ (2018) Do channels matter?Journalism Studies19: 2359–2378.
46.
VragaEKBodeLTullyM (2022) Creating news literacy messages to enhance expert corrections of misinformation on Twitter. Communication Research49: 245–267.
47.
VragaEKTullyMKotcherJE, et al. (2015) A multi-dimensional approach to measuring news media literacy. Journal of Media Literacy Education7: 41–53.
48.
VragaEKTullyMMakslA, et al. (2021) Theorizing news literacy behaviors. Communication Theory31: 1–21.
49.
WalterNCohenJHolbertRL, et al. (2020) Fact-checking: a meta-analysis of what works and for whom. Political Communication37: 350–375.
50.
ZallerJR (1992) The Nature and Origins of Mass Opinion. Cambridge: Cambridge University Press.
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.
