Seeing Is Believing: Is Video Modality More Powerful in Spreading Fake News via Online Messaging Apps?
Open accessAbstract
Abstract False rumors on WhatsApp, the world’s largest messaging app, have led to mob lynching in India and other countries. Doctored videos sent over the platform have elicited visceral responses among users, resulting in the wrongful death of innocent people. Would the responses have been so strong if the false news were circulated in text or audio? Is video modality the reason for such powerful effects? We explored this question by comparing reactions to three false stories prepared in either text-only, audio-only, or video formats, among rural and urban users in India. Our findings reveal that video is processed more superficially, and therefore users believe in it more readily and share it with others. Aside from advancing our theoretical understanding of modality effects in the context of mobile media, our findings also hold practical implications for design of modality-based flagging of fake news, and literacy campaigns to inoculate users against misinformation.
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Processing videos that combine different modalities can result in cognitive overload, as many cognitive resources are devoted to encoding, at the cost of systematically processing substantial arguments of the message.
“The processing of videos that combine different modalities can result in cognitive overload, as many cognitive resources are devoted to encoding. This comes at the cost of systematically processing substantial arguments of the message (Sundar et al., 2021).”
From How persuasive are political cheapfakes disseminated via social media? The effects of out-of-context visual disinformation on message credibility and issue agreement (2025) · cites this paper as Sundar et al., 2021
The realism heuristic predicts that people are more likely to trust audiovisual modality relative to text because its content has a higher resemblance to the real world.
“The realism heuristic29,31 predicts that “people are more likely to trust audiovisual modality [relative to text] because its content has a higher resemblance to the real world.””
From Human detection of political speech deepfakes across transcripts, audio, and video (2024) · cites this paper as [29]
The emotional and motivational influences of visual communication have been attributed to why misleading viral videos have provoked mob-violence.
“the emotional and motivational influences of visual communication have been attributed to why misleading viral videos have provoked mob-violence28,29.”
From Human detection of political speech deepfakes across transcripts, audio, and video (2024) · cites this paper as [29]
In an experiment using 3 false news videos, stories presented as videos are perceived as more credible than stories presented as text or read aloud in audio.
“In an experiment using 3 false news videos as stimuli, researchers found that stories presented as videos are perceived as more credible than stories presented as text or read aloud in audio form29.”
From Human detection of political speech deepfakes across transcripts, audio, and video (2024) · cites this paper as [29]
Cites
Basics of Qualitative Research (3rd ed.): Techniques and Procedures for Developing Grounded Theory
Corbin, J., & Strauss, A. (2008) · SAGE · doi:10.4135/9781452230153 · Cited by 12,136 · see citing works
(2008) · Cited by 7,674 · see citing works
Confirmation Bias: A Ubiquitous Phenomenon in Many Guises
Nickerson, R. S. (1998) · Review of General Psychology · doi:10.1037/1089-2680.2.2.175 · Cited by 7,267 · see citing works
Chakravarti, D., Eagly, A. H., & Chaiken, S. (1997) · Journal of Marketing Research · doi:10.2307/3151869 · Cited by 7,169 · see citing works
Bower, G. H. (1981) · American Psychologist · doi:10.1037//0003-066x.36.2.129 · Cited by 5,798 · see citing works
Chaiken, S. (1980) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.39.5.752 · Cited by 5,516 · see citing works
Bower, G. H. (1981) · American Psychologist · doi:10.1037/0003-066x.36.2.129 · Cited by 4,154 · see citing works
The limited capacity model of mediated message processing
Lang, A. (2000) · Journal of Communication · doi:10.1111/j.1460-2466.2000.tb02833.x · Cited by 2,153 · see citing works
Less than you think: Prevalence and predictors of fake news dissemination on Facebook
Guess, A., Nagler, J., & Tucker, J. (2019) · Science Advances · doi:10.1126/sciadv.aau4586 · Cited by 1,652 · see citing works
Social and Heuristic Approaches to Credibility Evaluation Online
Metzger, M. J., Flanagin, A. J., & Medders, R. B. (2010) · Journal of Communication · doi:10.1111/j.1460-2466.2010.01488.x · Cited by 1,394 · see citing works
Public health and online misinformation: challenges and recommendations
Swire-Thompson, B., & Lazer, D. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094127 · Cited by 1,170 · see citing works
Digital Media, Youth, and Credibility
Metzger, M. J., & Flanagin, A. J. (2007) · Cited by 1,036 · see citing works
Science audiences, misinformation, and fake news
Scheufele, D. A., & Krause, N. M. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1805871115 · Cited by 878 · see citing works
Fake news and COVID-19: modelling the predictors of fake news sharing among social media users
Apuke, O. D., & Omar, B. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2020.101475 · Cited by 773 · see citing works
AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations
Hancock, J. T., Naaman, M., & Levy, K. (2020) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmz022 · Cited by 658 · see citing works
A comparative analysis of four scales of consumer involvement
Mittal, B. (1995) · Psychology and Marketing · doi:10.1002/mar.4220120708 · Cited by 649 · see citing works
Talwar, S., Dhir, A., Kaur, P., Zafar, N., & Alrasheedy, M. (2019) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2019.05.026 · Cited by 577 · see citing works
Processing political misinformation: comprehending the Trump phenomenon
Swire‐Thompson, B., Berinsky, A. J., Lewandowsky, S., & Ecker, U. K. H. (2017) · Royal Society Open Science · doi:10.1098/rsos.160802 · Cited by 499 · see citing works
“Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content
Molina, M. D., Sundar, S. S., Le, T., & Lee, D. (2021) · American Behavioral Scientist · doi:10.1177/0002764219878224 · Cited by 485 · see citing works
Self-citationThe facts of fake news: A research review
Tandoc, E. C. (2019) · Sociology Compass · doi:10.1111/soc4.12724 · Cited by 326 · see citing works
Sundar, S. S. (2000) · Journalism & Mass Communication Quarterly · doi:10.1177/107769900007700302 · Cited by 308 · see citing works
Self-citationToo good to be true, too good not to share: the social utility of fake news
Duffy, A. M., Tandoc, E. C., & Ling, R. (2019) · Information Communication & Society · doi:10.1080/1369118x.2019.1623904 · Cited by 303 · see citing works
Measuring Trust In Advertising
Soh, H., Reid, L. N., & King, K. W. (2009) · Journal of Advertising · doi:10.2753/joa0091-3367380206 · Cited by 262 · see citing works
Presence and Reality Judgment in Virtual Environments: A Unitary Construct?
Baños, R. M., Botella, C., Garcia-Palacios, A., Villa, H., Perpiña, C., & Alcañiz, M. (2000) · CyberPsychology & Behavior · doi:10.1089/10949310050078760 · Cited by 254 · see citing works
Luo, M., Hancock, J. T., & Markowitz, D. M. (2022) · Communication Research · doi:10.1177/0093650220921321 · Cited by 245 · see citing works
Global patterns and drivers of ecosystem functioning in rivers and riparian zones
Tiegs, S. D., Costello, D. M., Isken, M. W., Woodward, G., McIntyre, P. B., Gessner, M. O., Chauvet, E., Griffiths, N. A., Flecker, A. S., Acuña, V., et al. (2019) · Science Advances · doi:10.1126/sciadv.aav0486 · Cited by 233 · see citing works
Oh, J., & Sundar, S. (2015) · Journal of Communication · doi:10.1111/jcom.12147 · Cited by 224 · see citing works
Self-citationHansen, J., & Wänke, M. (2010) · Personality and Social Psychology Bulletin · doi:10.1177/0146167210386238 · Cited by 198 · see citing works
Political Attitudes and the Processing of Misinformation Corrections
Ecker, U. K. H., & Ang, L. C. (2018) · Political Psychology · doi:10.1111/pops.12494 · Cited by 175 · see citing works
Yadav, A., Phillips, M. M., Lundeberg, M. A., Koehler, M. J., Hilden, K., & Dirkin, K. H. (2011) · Journal of Computing in Higher Education · doi:10.1007/s12528-011-9042-y · Cited by 127 · see citing works
Appiah, O. (2006) · Journal of Current Issues & Research in Advertising · doi:10.1080/10641734.2006.10505192 · Cited by 122 · see citing works
Lee, E. J., & Kim, Y. W. (2015) · New Media & Society · doi:10.1177/1461444814567982 · Cited by 119 · see citing works
Banaji, S., Bhat, R., Agarwal, A., Passanha, N. K. J., & Pravin, M. (2019) · London School of Economics and Political Science Research Online (London School of Economics and Political Science) · Cited by 119 · see citing works
Chimpanzees recognize their own delayed self-image
Hirata, S., Fuwa, K., & Myowa, M. (2017) · Royal Society Open Science · doi:10.1098/rsos.170370 · Cited by 99 · see citing works
Enhancing motivation, ability, and opportunity to process public relations messages
Hallahan, K. (2000) · Public Relations Review · doi:10.1016/s0363-8111(00)00059-x · Cited by 96 · see citing works
Misinformation and Mass Audiences
(2018) · University of Texas Press eBooks · doi:10.7560/314555 · Cited by 87 · see citing works
Pierro, A., Mannetti, L., Kruglanski, A. W., & Sleeth‐Keppler, D. (2004) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.86.2.251 · Cited by 57 · see citing works
Video Killed the News Article? Comparing Multimodal Framing Effects in News Videos and Articles
Powell, T. E., Boomgaarden, H. G., De Swert, K., & de Vreese, C. H. (2018) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2018.1483935 · Cited by 46 · see citing works
Modality-Specific Effects of Perceptual Load in Multimedia Processing
Fisher, J. T., Hopp, F. R., & Weber, R. (2019) · Media and Communication · doi:10.17645/mac.v7i4.2388 · Cited by 29 · see citing works
Technological Affordances Can Promote Misinformation
Molina, M. D., & Sundar, S. S. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190900250.003.0013 · Cited by 17 · see citing works
Self-citationJournalism and Truth in an Age of Social Media
Katz, J. E., & Mays, K. K. (2019) · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Qi, P., Bu, Y., Cao, J., Ma, W. J., Shui, R., Xiao, J., Wang, D., & Chua, T. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i12.26689 · Cited by 116 · see citing works
The (minimal) persuasive advantage of political video over text
Wittenberg, C., Tappin, B. M., Berinsky, A. J., & Rand, D. G. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2114388118 · Cited by 114 · see citing works
Koch, T. K., Frischlich, L., & Lermer, E. (2023) · Journal of Applied Social Psychology · doi:10.1111/jasp.12959 · Cited by 109 · see citing works
Creating, Using, Misusing, and Detecting Deep Fakes
Farid, H. (2022) · Journal of Online Trust and Safety · doi:10.54501/jots.v1i4.56 · Cited by 92 · see citing works
Lee, J., & Shin, S. Y. (2022) · Media Psychology · doi:10.1080/15213269.2021.2007489 · Cited by 89 · see citing works
Melchior, C., & Oliveira, M. F. D. A. (2023) · New Media & Society · doi:10.1177/14614448231174224 · Cited by 77 · see citing works
Human detection of political speech deepfakes across transcripts, audio, and video
Groh, M., Sankaranarayanan, A., Singh, N., Kim, D. Y., Lippman, A., & Picard, R. (2024) · Nature Communications · doi:10.1038/s41467-024-51998-z · Cited by 89 · see citing works
Combating Fake News: Stakeholder Interventions and Potential Solutions
Gupta, A. K., Kumar, N., Prabhat, P., Gupta, R., Tanwar, S., Sharma, G., Bokoro, P. N., & Sharma, R. (2022) · IEEE Access · doi:10.1109/access.2022.3193670 · Cited by 68 · see citing works
Hameleers, M., van der Meer, T. G. L. A., & Dobber, T. (2022) · Social Media + Society · doi:10.1177/20563051221116346 · Cited by 67 · see citing works
An Agenda for Studying Credibility Perceptions of Visual Misinformation
Peng, Y.-L., Lu, Y.-D., & Shen, C.-H. (2023) · Political Communication · doi:10.1080/10584609.2023.2175398 · Cited by 62 · see citing works
A Systematic Review Of COVID-19 Misinformation Interventions: Lessons Learned
Smith, R., Chen, K., Winner, D., Friedhoff, S., & Wardle, C. (2023) · Health Affairs · doi:10.1377/hlthaff.2023.00717 · Cited by 53 · see citing works
Hameleers, M., van der Meer, T. G. L. A., & Dobber, T. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.108096 · Cited by 66 · see citing works
FakingRecipe: Detecting Fake News on Short Video Platforms from the Perspective of Creative Process
Bu, Y., Sheng, Q., Cao, J., Qi, P., Wang, D., & Li, J. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3680663 · Cited by 50 · see citing works
Fake News in Virtual Community, Virtual Society, and Metaverse: A Survey
Wang, J., Makowski, S., Cieślik, A., Lv, H., & Lv, Z. (2023) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2022.3220420 · Cited by 49 · see citing works
They Would Never Say Anything Like This! Reasons To Doubt Political Deepfakes
Hameleers, M., van der Meer, T. G. L. A., & Dobber, T. (2024) · European Journal of Communication · doi:10.1177/02673231231184703 · Cited by 47 · see citing works
He, Q., Zhang, S., Cai, Y., Yuan, W., Ma, L., & Yu, K. (2025) · ACM Computing Surveys · doi:10.1145/3716498 · Cited by 45 · see citing works
Mitigating World Biases: A Multimodal Multi-View Debiasing Framework for Fake News Video Detection
Zeng, Z., Luo, M., Kong, X., Liu, H., Guo, H., Yang, H., Ma, Z., & Zhao, X. H. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681673 · Cited by 44 · see citing works
Do Bandwagon Cues Affect Credibility Perceptions? A Meta-Analysis of the Experimental Evidence
Wang, S., Chu, T. H., & Huang, G. (2023) · Communication Research · doi:10.1177/00936502221124395 · Cited by 49 · see citing works
Combating Online Misinformation Videos: Characterization, Detection, and Future Directions
Bu, Y., Sheng, Q., Cao, J., Qi, P., Wang, D., & Li, J. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612426 · Cited by 42 · see citing works
Labeling AI-generated media online
Wittenberg, C. E., Epstein, Z., Péloquin-Skulski, G., Berinsky, A. J., & Rand, D. G. (2025) · PNAS Nexus · doi:10.1093/pnasnexus/pgaf170 · Cited by 49 · see citing works
The Liar’s Dividend: Can Politicians Claim Misinformation to Evade Accountability?
Schiff, K. J., Schiff, D. S., & Bueno, N. S. (2024) · American Political Science Review · doi:10.1017/s0003055423001454 · Cited by 39 · see citing works
After Deception: How Falling for a Deepfake Affects the Way We See, Hear, and Experience Media
Weikmann, T., Greber, H., & Nikolaou, A. (2024) · The International Journal of Press/Politics · doi:10.1177/19401612241233539 · Cited by 39 · see citing works
Hou, T.-Y., Tseng, Y.-C., & Yuan, C. W. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102775 · Cited by 41 · see citing works
”It Matches My Worldview”: Examining Perceptions and Attitudes Around Fake Videos
Shahid, F., Kamath, S., Sidotam, A., Jiang, V., Batino, A., & Vashistha, A. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517646 · Cited by 40 · see citing works
Lee, J., Hameleers, M., & Shin, S. Y. (2023) · New Media & Society · doi:10.1177/14614448231153959 · Cited by 37 · see citing works
Jin, X., Zhang, Z., Gao, B., Gao, S., Zhou, W., Yu, N., & Wang, G. (2023) · New Media & Society · doi:10.1177/14614448231199664 · Cited by 34 · see citing works
Beege, M., Krieglstein, F., & Arnold, C. (2022) · Computers & Education · doi:10.1016/j.compedu.2022.104531 · Cited by 34 · see citing works
Missing the Bigger Picture: The Need for More Research on Visual Health Misinformation
Heley, K. M., Gaysynsky, A., & King, A. J. (2022) · Science Communication · doi:10.1177/10755470221113833 · Cited by 34 · see citing works
Two Heads Are Better Than One: Improving Fake News Video Detection by Correlating with Neighbors
Qi, P., Zhao, Y., Shen, Y., Ma, W. J., Cao, J., & Chua, T. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.756 · Cited by 43 · see citing works
Ross, A. A., Badrinathan, S., Mont’Alverne, C., Toff, B., Fletcher, R., & Nielsen, R. K. (2023) · Journalism · doi:10.1177/14648849231194485 · Cited by 48 · see citing works
Cheap Versus Deep Manipulation: The Effects of Cheapfakes Versus Deepfakes in a Political Setting
Hameleers, M. (2024) · International Journal of Public Opinion Research · doi:10.1093/ijpor/edae004 · Cited by 32 · see citing works
Televised Oral Arguments and Judicial Legitimacy: An Initial Assessment
Black, R. C., Johnson, T. R., Owens, R. J., & Wedeking, J. (2023) · Political Behavior · doi:10.1007/s11109-022-09848-5 · Cited by 31 · see citing works
Factors Associated With Information Credibility Perceptions: A Meta-Analysis
Ou, M., & Ho, S. S. (2024) · Journalism & Mass Communication Quarterly · doi:10.1177/10776990231222556 · Cited by 37 · see citing works
Hameleers, M. (2024) · Political Communication · doi:10.1080/10584609.2024.2354389 · Cited by 30 · see citing works
Perception and deception: Exploring individual responses to deepfakes across different modalities
Ahmed, S., & Chua, H. W. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e20383 · Cited by 29 · see citing works
Lind, S. J. (2024) · Journal of Workplace Learning · doi:10.1108/jwl-04-2024-0075 · Cited by 26 · see citing works
Gamified Inoculation Against Misinformation in India: A Randomized Control Trial
Harjani, T., Basol, M., Roozenbeek, J., & van der Linden, S. (2023) · Journal of Trial and Error · doi:10.36850/e12 · Cited by 26 · see citing works
How effective are TikTok misinformation debunking videos?
Bhargava, P., MacDonald, K., Newton, C., Lin, H., & Pennycook, G. (2023) · Harvard Kennedy School Misinformation Review · doi:10.37016/mr-2020-114 · Cited by 26 · see citing works
Sui, M., Hawkins, I., & Wang, R. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107654 · Cited by 24 · see citing works
Misinformation in Virtual Reality
Brown, J., Bailenson, J. N., & Hancock, J. T. (2023) · Journal of Online Trust and Safety · doi:10.54501/jots.v1i5.120 · Cited by 30 · see citing works
WaterLo: Protect Images from Deepfakes Using Localized Semi-Fragile Watermark
Beuve, N., Hamidouche, W., & Olivier Déforges, A. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00046 · Cited by 24 · see citing works
Disinformation on the COVID-19 pandemic and the Russia-Ukraine War: Two sides of the same coin?
del Vas, R. S., & Navarro, J. T. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03355-0 · Cited by 23 · see citing works
Lee, J., & Hameleers, M. (2024) · Media Psychology · doi:10.1080/15213269.2024.2401539 · Cited by 21 · see citing works
Dan, V. (2025) · The International Journal of Press/Politics · doi:10.1177/19401612251317766 · Cited by 22 · see citing works
Multimodal analysis of disinformation and misinformation
Wilson, A., Wilkes, S., Teramoto, Y., & Hale, S. A. (2023) · Royal Society Open Science · doi:10.1098/rsos.230964 · Cited by 24 · see citing works
The Mobilizing Power of Visual Media Across Stages of Social-Mediated Protests
Lu, Y., & Peng, Y. (2024) · Political Communication · doi:10.1080/10584609.2024.2317951 · Cited by 22 · see citing works
Do people believe in misleading information disseminated via memes? The role of identity and anger
Molina, M. D. (2023) · New Media & Society · doi:10.1177/14614448231186061 · Cited by 18 · see citing works
Self-citationHardin, A. E., Schinoff, B. S., Byron, K., & Balven, R. M. (2024) · Academy of Management Journal · doi:10.5465/amj.2022.0683 · Cited by 16 · see citing works
Hameleers, M. (2024) · Journal of Communication · doi:10.1093/joc/jqae045 · Cited by 16 · see citing works
Friedman, R. S., & Campbell, D. S. (2023) · Environmental Communication · doi:10.1080/17524032.2023.2215959 · Cited by 15 · see citing works
Shibuya, Y., Nakazato, T., & Takagi, S. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103485 · Cited by 16 · see citing works
Farooq, A., & de Vreese, C. H. (2025) · AI & Society · doi:10.1007/s00146-025-02416-5 · Cited by 21 · see citing works
Walther, J. B., Lew, Z., Edwards, A. L., & Quick, J. (2022) · Journal of Communication · doi:10.1093/joc/jqac033 · Cited by 15 · see citing works
Hameleers, M., Harff, D., & Schmuck, D. (2023) · Digital Journalism · doi:10.1080/21670811.2023.2210616 · Cited by 15 · see citing works
Game On: Enhancing Customer Engagement Through Influencers’ Gamified Messages
Kapoor, P. S., Balaji, M. S., & Maity, M. (2024) · Journal of Travel Research · doi:10.1177/00472875241289565 · Cited by 14 · see citing works
Alon, A. T., Rahimi, I. D., & Tahar, H. (2025) · Online Information Review · doi:10.1108/oir-07-2024-0445 · Cited by 13 · see citing works
Gaiser, F., & Utz, S. (2023) · Journal of Media Psychology Theories Methods and Applications · doi:10.1027/1864-1105/a000384 · Cited by 13 · see citing works
Xu, Z., Jahng, S., & Liang, L. (2024) · Current Psychology · doi:10.1007/s12144-024-06144-9 · Cited by 13 · see citing works
Dan, V., & Coleman, R. (2024) · Communication Research · doi:10.1177/00936502241287870 · Cited by 13 · see citing works
Kim, D., Choi, M., & Choi, Y. (2025) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2025.2507944 · Cited by 13 · see citing works
Lee, N., Hong, Y., Hu, S., Kirkpatrick, C. E., Lee, S., & Hinnant, A. (2024) · Journal of Health Communication · doi:10.1080/10810730.2024.2339237 · Cited by 12 · see citing works
Whittaker, L., Kietzmann, J., Letheren, K., Mulcahy, R. F., & Russell‐Bennett, R. (2022) · Business Horizons · doi:10.1016/j.bushor.2022.07.004 · Cited by 12 · see citing works
Correction by distraction: how high-tempo music enhances medical experts’ debunking TikTok videos
Li, M., Li, G., & Yang, S. (2024) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmae007 · Cited by 15 · see citing works
Hu, L., Wang, Z., Zhu, J., Zhu, J., & Wang, X. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114298 · Cited by 11 · see citing works
Hameleers, M., van der Meer, T., & Vliegenthart, R. (2025) · Information, Communication & Society · doi:10.1080/1369118x.2024.2388079 · Cited by 10 · see citing works
“This comes at the cost of systematically processing substantial arguments of the message (Sundar et al., 2021).”
Fake News in the Post-COVID-19 Era? The Health Disinformation Agenda in Spain
Costa-Sánchez, C., Vizoso, Á., & García, X. L. (2023) · Societies · doi:10.3390/soc13110242 · Cited by 10 · see citing works
George, N., Sham, A., Ajith, T., & Bastos, M. (2024) · Social Science Computer Review · doi:10.1177/08944393241269394 · Cited by 9 · see citing works
Beyond Credibility: The Effects of Different Forms of Visual Disinformation
Weikmann, T., Egelhofer, J. L., & Lecheler, S. K. (2025) · Journalism & Mass Communication Quarterly · doi:10.1177/10776990251357299 · Cited by 9 · see citing works
Conclusion: Misinformation and AI—How Algorithms Generate and Manipulate Misinformation
Shin, D. (2024) · Springer eBooks · doi:10.1007/978-3-031-52569-8_10 · Cited by 9 · see citing works
Zenouzagh, Z. M., Admiraal, W., & Saab, N. (2024) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13010 · Cited by 9 · see citing works
The Liar’s Dividend: Can Politicians Claim Misinformation to Evade Accountability?
Schiff, K. J., Schiff, D. S., & Bueno, N. (2023) · doi:10.31235/osf.io/x43ph · Cited by 8 · see citing works
Lee, J., & Suk, J. (2025) · Communication Theory · doi:10.1093/ct/qtaf011 · Cited by 11 · see citing works
Kang, S., & Valadez, K. (2025) · Journalism & Mass Communication Quarterly · doi:10.1177/10776990251357294 · Cited by 8 · see citing works
von Sikorski, C., & Hameleers, M. (2025) · Journalism & Mass Communication Quarterly · doi:10.1177/10776990251375097 · Cited by 8 · see citing works
Investigating Correction Effects of Different Modalities for Misinformation about COVID-19
Tseng, Y.-C., Bi, N., Chang, Y.-J., & Yuan, C. W. (2022) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/3500868.3559455 · Cited by 8 · see citing works
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Beuve, N., Hamidouche, W., & Olivier Déforges, A. (2023) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3626101 · Cited by 8 · see citing works
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Liu, Q., Wang, L., & Luo, M. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04594-5 · Cited by 8 · see citing works
Chan, M., Yi, J., Vaccari, C., & Yamamoto, M. (2025) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmaf009 · Cited by 7 · see citing works
Chen, Z., Ye, J., Tsai, B., Ferrara, E., & Luceri, L. (2025) · ACM Conference on Hypertext and Social Media (HT) · doi:10.1145/3720553.3746675 · Cited by 7 · see citing works
Misinformation in India's 2019 National Election
Basavaraj, K. A. (2022) · Journal of Quantitative Description Digital Media · doi:10.51685/jqd.2022.021 · Cited by 7 · see citing works
Auditing Google's Search Headlines as a Potential Gateway to Misleading Content
Zade, H., Wack, M., Zhang, Y., Starbird, K., Calo, R., Young, J., & West, J. D. (2022) · Journal of Online Trust and Safety · doi:10.54501/jots.v1i4.72 · Cited by 8 · see citing works
Assessment of cognitive biases in augmented reality: Beyond eye tracking.
Słowiński, P., Grindley, B., Muncie, H., Harris, D., Vine, S. J., & Wilson, M. (2022) · Journal of Eye Movement Research · doi:10.16910/jemr.15.3.4 · Cited by 7 · see citing works
The Liar’s Dividend: Can Politicians Use Deepfakes and Fake News to Evade Accountability?
Schiff, K. J., Schiff, D. S., & Bueno, N. (2022) · doi:10.31235/osf.io/q6mwn · Cited by 6 · see citing works
Sun, Y., Pendyala, V., Lian, R., Xin, H., Patel, P., Bucy, E. P., & Shah, D. V. (2025) · Visual Communication Quarterly · doi:10.1080/15551393.2025.2455495 · Cited by 6 · see citing works
Ma, Y., Sarsenbayeva, Z., Knibbe, J., & Gonçalves, J. (2024) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2024.103378 · Cited by 6 · see citing works
Specific media literacy tips improve AI-generated visual misinformation discernment
Guo, S., Swire‐Thompson, B., & Hu, X. (2025) · Cognitive Research Principles and Implications · doi:10.1186/s41235-025-00648-z · Cited by 6 · see citing works
Yang, H.-P., Chan, T. K. H., Tran, H.-A., Nguyen, B., & Lin, H. Y. (2024) · Information Technology and People · doi:10.1108/itp-02-2023-0126 · Cited by 5 · see citing works
MMSFD: Multi-grained and Multi-modal Fusion for Short Video Fake News Detection
Ren, S., Liu, Y., Zhu, Y., Bing, W., Ma, H., & Wang, W. (2024) · International Conference on Data Science and Information Technology (DSIT) · doi:10.1109/dsit61374.2024.10881540 · Cited by 5 · see citing works
Consistency-Aware Fake Videos Detection on Short Video Platforms
Wang, J., Liu, J., Zhang, N., & Wang, Y. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-9812-7_17 · Cited by 5 · see citing works
Hu, B., & Huang, G. (2025) · Social Media + Society · doi:10.1177/20563051251401815 · Cited by 6 · see citing works
McDermott, Y., Hausknecht, A. C., & Liefgreen, A. (2026) · Oñati Socio-legal Series · doi:10.35295/osls.iisl.2375 · Cited by 6 · see citing works
CoFFEE: a codec-based forensic feature extraction and evaluation software for H.264 videos
Bertazzini, G., Baracchi, D., Shullani, D., Iuliani, M., & Piva, A. (2024) · EURASIP Journal on Information Security · doi:10.1186/s13635-024-00181-4 · Cited by 5 · see citing works
Meng, X., Dai, C., Zhao, Y., & Zhou, Y. (2023) · Library Hi Tech · doi:10.1108/lht-02-2023-0073 · Cited by 5 · see citing works
A fake news detection framework integrating multi-domain and multimodal features
Guo, L., Chen, Z., & Liu, X. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131711 · Cited by 4 · see citing works
Knowledge-Enhanced Dynamic Scene Graph Attention Network for Fake News Video Detection
Huang, X., Ma, T., Tang, H., & Rong, H. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3623491 · Cited by 4 · see citing works
23 Algorithms and Affordances: Psychology of Human–AI Interaction
Sundar, S. S., Liao, M., & Lee, S. (2025) · De Gruyter eBooks · doi:10.1515/9783111292144-029 · Cited by 4 · see citing works
Self-citationSharman, S. J., Danby, M. C., & Gray, A. D. (2023) · Memory · doi:10.1080/09658211.2023.2294692 · Cited by 4 · see citing works
Too Good to be False: How Photorealism Promotes Susceptibility to Misinformation
Jang, E., Lee, H. M., Lee, S., Jung, Y., & Sundar, S. S. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3719796 · Cited by 4 · see citing works
Self-citationGreber, H., Aaldering, L., & Lecheler, S. K. (2024) · Media and Communication · doi:10.17645/mac.8571 · Cited by 4 · see citing works
When Seeing Isn’t Believing: Navigating Visual Health Misinformation through Library Instruction
Cowles, K., Miller, R. S., & Suppok, R. (2024) · Medical Reference Services Quarterly · doi:10.1080/02763869.2024.2290963 · Cited by 4 · see citing works
- Authors
- Sundar, S. S., Molina, M. D., & Cho, E.
- Affiliations
- Pennsylvania State University (US)
- Department of Advertising and Public Relations, Michigan State University, East Lansing, MI 48824, USA
- The College of New Jersey (US)
- Corresponding author
- Sundar, S Shyam
- Venue
- Journal of Computer-Mediated Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-08-01
- Volume
- 26
- Issue
- 6
- Pages
- 301-319
- ISSN
- 1083-6101 (ISSN-L)
- OpenAlex
- W3188473680
- Cited by
- 212
- References
- 41
- Citations by year
- 2026: 49 · 2025: 62 · 2024: 42 · 2023: 38 · 2022: 19 · 2021: 2
- FWCI
- 34.99
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Journal of Computer-Mediated Communication (publishedVersion, cc-by)
- Funders
- University of Pennsylvania
- Pennsylvania State University
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Sociology and Political Science › Islamic Finance and Communication
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Keywords
- fake news, misinformation, WhatsApp, messaging apps, belief in misinformation, urban-rural differences, misinformation literacy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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