St. Petersburg, Russian Federation
St. Petersburg, Russian Federation
UDC 316
UDC 81
UDC 159.9
CSCSTI 04.00
CSCSTI 15.00
CSCSTI 16.00
The digital era has drastically transformed how people consume and share news. This has led to an unprecedented spread of misinformation that is difficult for the public to identify. While research on journalistic and automated fact-checking is extensive, the ordinary internet users’ strategies remain underexplored. This study bridges the gap by investigating both internal (intrinsic cues) and external (extrinsic verification) fact-checking strategies through a mixed-methods approach. Qualitative cognitive interviews with 42 participants revealed an extensive list of intrinsic heuristics. A quantitative pilot survey of 150 respondents highlighted the prominence of extrinsic strategies. Results indicated the following: 76% of participants prioritize lateral reading, 57% verify information in trusted sources, 50% seek expert opinions, and only 21% consult with peers (this is less common). Qualitative analysis further uncovered a key finding. Intrinsic assessments often rely on subjective metadata cues and confirmation bias, sometimes leading to contradictory judgments. This research emphasized the need for a holistic understanding of fact-checking behaviors. It also laid the groundwork for further studies on the effectiveness of such behaviors in improving media literacy.
fact-checking strategies, fake news, news credibility assessment, digital misinformation, media literacy
1. Baumann F., Lorenz-Spreen P., Sokolov I. M., Starnini M. Modeling echo chambers and polarization dynamics in social networks. Physical Review Letters, 124(4). https://doi.org/10.1103/physrevlett.124.048301
2. Benkler Y., Faris R., Roberts H. Network propaganda: Manipulation, disinformation, and radicalization in American politics. NY: Oxford University Press, 2018, 472. https://doi.org/10.1093/oso/9780190923624.001.0001
3. Bradshaw S., Howard P. N. The global disinformation order: 2019 global inventory of organized social media manipulation. Online: University of Oxford, 2019. URL: https://demtech.oii.ox.ac.uk/wp-content/uploads/sites/93/2019/09/CyberTroop-Report19.pdf (accessed 1 Mar 2026).
4. Broersma M. A refractured paradigm. Journalism, hoaxes and the challenge of trust. Rethinking journalism: Trust and participation in a transformed news landscape, eds. Broersma M., Peters C. London: Routledge, 2013, 28–44.
5. Broersma M. Journalism as performative discourse. The importance of form and style in journalism. Journalism and meaning-making: Reading the newspaper, ed. Rupar V. NY: Hampton Press, 2010, 15–35.
6. Burki T. Vaccine misinformation and social media. The Lancet Digital Health, 2019, 1(6). https://doi.org/10.1016/S2589-7500(19)30136-0
7. DeVerna M. R., Yan H. Y., Yang K.-C., Menczer F. Fact-checking information from large language models can decrease headline discernment. Proceedings of the National Academy of Sciences, 2024, 121(50). https://doi.org/10.1073/pnas.2322823121
8. Druckman J. N., Levendusky M. S., McLain A. No need to watch: How the effects of partisan media can spread via inter-personal discussions. American Journal of Political Science, 2017, 62(2). https://doi.org/10.1111/ajps.12325
9. Duncan M. The effectiveness of credibility indicator interventions in a partisan context. Newspaper Research Journal, 2019, 40(4). https://doi.org/10.1177/0739532919873707
10. Fazio L., Rand D., Lewandowsky S., Susmann M., Berinsky A. J., Guess A., Kendeou P., Lyons B., Miller J. M., Newman E. Combating misinformation: A megastudy of nine interventions designed to reduce the sharing of and belief in false and misleading headlines. PsyArXiv, 2024. https://doi.org/10.31234/osf.io/uyjha
11. Guo Z., Schlichtkrull M., Vlachos A. A survey on automated fact-checking. Transactions of the Association for Computational Linguistics, 2022, 10: 178–206. https://doi.org/10.1162/tacl_a_00454
12. Henke J., Leissner L., Möhring W. How can journalists promote news credibility? Effects of evidence on trust and credibility. Journalism Practice, 2020, 14(3): 299–318. https://doi.org/10.1080/17512786.2019.1605839
13. Hovland C. I., Weiss W. The influence of source credibility on communication effectiveness. Public Opinion Quarterly, 1951, 15(4): 635–650. https://doi.org/10.1086/266350
14. Inglehart R. F. Cultural evolution: People’s motivations are changing, and reshaping the world. Cambridge: Cambridge University Press, 2018, 288.
15. Kavanagh J., Rich M. D. Truth decay: An initial exploration of the diminishing role of facts and analysis in American public life. RAND, 2018. https://doi.org/10.7249/RR2314
16. Lim C. Checking how fact-checkers check. Research & Politics, 2018, 5(3). https://doi.org/10.1177/2053168018786848
17. Martel C., Allen J., Pennycook G., Rand D. G. Crowds can effectively identify misinformation at scale. Perspectives on Psychological Science, 2024, 19(2): 477–488. https://elibrary.ru/hekdji
18. Morris M. R., Counts S., Roseway A., Hoff A., Schwarz J. Tweeting is believing?: Understanding microblog credibility perceptions. Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, Seattle, 11–15 Feb 2012. NY: ACM, 2012, 441–450. https://doi.org/10.1145/2145204.2145274
19. Nickerson R. S. Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 1998, 2(2): 175–220. https://doi.org/10.1037/1089-2680.2.2.175
20. Nogara G., Vishnuprasad P. S., Cardoso F., Ayoub O., Giordano S., Luceri L. The disinformation dozen: An exploratory analysis of COVID-19 disinformation proliferation on Twitter. Proceedings of the 14th ACM Web Science Conference, 2022, 348–358. https://doi.org/10.1145/3501247.3531573
21. Nyhan B., Reifler J. When corrections fail: The persistence of political misperceptions. Political Behavior, 2010, 32(2): 303–330. https://doi.org/10.1007/s11109-010-9112-2
22. Ognyanova K. The social context of media trust: A network influence model. Journal of Communication, 2019, 69(5): 539–562. https://doi.org/10.1093/joc/jqz031
23. Panizza F., Ronzani P., Martini C., Mattavelli S., Morisseau T., Motterlini M. Lateral reading and monetary incentives to spot disinformation about science. Scientific Reports, 2022, 12. https://doi.org/10.1038/s41598-022-09168-y
24. Puustinen L., Seppänen J. The image of trust: Readers’ views on the trustworthiness of news photographs. CM – Casopis Za Upravljanje Komuniciranjem, 2013, 8(26): 11–32. https://doi.org/10.5937/comman1326011P
25. Quelle D., Bovet A. The perils and promises of fact-checking with large language models. Frontiers in Artificial Intelligence, 2024, (7). https://doi.org/10.3389/frai.2024.1341697
26. Rossini P., Stromer-Galley J., Baptista E. A., Veiga de Oliveira V. Dysfunctional information sharing on WhatsApp and Facebook. New Media & Society, 2021, 23(8): 2430–2451. https://doi.org/10.1177/1461444820928059
27. Shariff S. M., Zhang X., Sanderson M. On the credibility perception of news on Twitter: Readers, topics, and features. Computers in Human Behavior, 2017, 75: 785–796. https://doi.org/10.1016/j.chb.2017.06.026
28. Spezzano F., Shrestha A., Fails J. A., Stone B. W. That’s fake news! Reliability of News When Provided Title, Image, Source Bias & Full Article. Proceedings of the ACM on Human-Computer Interaction, 2021, 5(CSCW1). https://doi.org/10.1145/3449183
29. Spitale G., Biller-Andorno N., Germani F. AI model GPT-3 (dis)informs us better than humans. Science Advances, 2023, 9(26). https://doi.org/10.1126/sciadv.adh1850
30. Swart J., Broersma M. The trust gap: Young people’s tactics for assessing the reliability of political news. The International Journal of Press/Politics, 2022, 27(2): 396–416. https://doi.org/10.1177/19401612211006696
31. Vosoughi S., Roy D., Aral S. The spread of true and false news online. Science, 2018, 359(6380): 1146–1151. https://doi.org/10.1126/science.aap9559
32. Walter N., Cohen J., Holbert R. L., Morag Y. Fact-checking: A meta-analysis of what works and for whom. Political Communication, 2020, 37(3): 350–375. https://doi.org/10.1080/10584609.2019.1668894
33. Wojdynski B. W., Binford M. T., Jefferson B. N. Looks real, or really fake? Warnings, Visual Attention and Detection of False News Articles. Open Information Science, 2019, 3(1): 166–180. https://doi.org/10.1515/opis-2019-0012
34. Zeng X., Abumansour A. S., Zubiaga A. Automated fact-checking: A survey. Language and Linguistics Compass, 2021, 15(10). https://doi.org/10.1111/lnc3.12438




