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Articles
Published: 2026-04-29

Media influence and user behaviour in the news environment: Traditional versus social media

Kozminski University, Poland; Széchenyi István University, Hungary
Kozminski University, Poland
National University of Water and Environmental Engineering, Ukraine
Kozminski University, Poland
Széchenyi Istvàn University, Hungary
digitalisation disinformation Eurobarometer 2025 social media traditional media algorithmic news fake news recognition

Abstract

This study investigates behavioural patterns in identifying disinformation within news environments, where algorithmically curated information flows shape human-technology interaction. Using data from the 2025 Eurobarometer survey (n=26,114), the research employs statistical analysis to compare users' attitudes towards news in traditional and social media. Findings indicate a significant disparity: while 65.9 % of respondents express high confidence in recognising fake news, 34.1% remain unconfident. Notably, high engagement with social media correlates with a greater exposure to disinformation. Women tend to have slightly higher self-reported exposure to disinformation (23.8%) than men (21.1%). Results demonstrate that demographic factors, particularly age and years of education, significantly shape information-checking behaviours. By adopting a human-oriented perspective, the study highlights how digitally mediated environments structure users’ interaction with information and condition their capacity to critically assess its reliability.

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References

  1. Alsyoof, S. M. S., László, V., & Sneider, T. (2025). Humane oriented CSR on social media: The roles of other praising emotions and social justice values. Journal of International Studies, 18(3), 46-67. https://doi.org/10.14254/2071-8330.2025/18-3/3 DOI: https://doi.org/10.14254/2071-8330.2025/18-3/3
  2. Altay, S., Berriche, A., & Acerbi, A. (2023). Misinformation on Misinformation: Conceptual and Methodological Challenges. Social Media + Society, 9(1). https://doi.org/10.1177/20563051221150412 DOI: https://doi.org/10.1177/20563051221150412
  3. Altay, S., Hoes, E., & Wojcieszak, M. (2025). Following news on social media boosts knowledge, belief accuracy and trust. Nature Human Behaviour, 9(9), 1833-1842. https://doi.org/10.1038/s41562-025-02205-6 DOI: https://doi.org/10.1038/s41562-025-02205-6
  4. Altay, S., Lyons, B. A., & Modirrousta-Galian, A. (2024). Exposure to higher rates of false news erodes media trust and fuels overconfidence. Mass Communication and Society, 28(2), 301-325. https://doi.org/10.1080/15205436.2024.2382776 DOI: https://doi.org/10.1080/15205436.2024.2382776
  5. Bacik, R., Gburova, J., Gavura, S., & Iannaccone, B. (2025). Impact of digital marketing on the purchasing behavior of modern consumers in the field of tourism. Journal of International Studies, 18(1), 116-129. https://doi.org/10.14254/2071- 8330.2025/18-1/7 DOI: https://doi.org/10.14254/2071-8330.2025/18-1/7
  6. Boczkowski, P. J., & Mitchelstein, E. (2021). The Digital Environment: How We Live, Learn, and Love Now. MIT Press. DOI: https://doi.org/10.7551/mitpress/13602.001.0001
  7. Bowes, S. M., Costello, T. H., & Tasimi, A. (2023). The conspiratorial mind: A meta-analytic review of motivational and personological correlates. Psychological Bulletin, 149(5-6), 259-293. https://doi.org/10.1037/bul0000392 DOI: https://doi.org/10.1037/bul0000392
  8. Cassells, R., Freyens, B.P., & Jenkins, P. (2024). Narcissistic prosociality in social media campaigns: Findings from a survey quasi- experiment. Economics and Sociology, 17(4), 159-175. https://doi.org/10.14254/2071-789X.2024/17-4/9 DOI: https://doi.org/10.14254/2071-789X.2024/17-4/9
  9. Chadwick, A. (2017). The Hybrid Media System. Oxford University Press. DOI: https://doi.org/10.1093/oso/9780190696726.001.0001
  10. Coutinho, F., Dias, A., & F. Pereira, L. (2023). Credibility of social media influencers: Impact on purchase intention. Human Technology, 19(2), 220–237. https://doi.org/10.14254/1795-6889.2023.19-2.5 DOI: https://doi.org/10.14254/1795-6889.2023.19-2.5
  11. Dreston, J. H., & Neubaum, G. (2023). How incidental and intentional news exposure in social media relate to political knowledge and voting intentions. Frontiers in Psychology, 14, 1–13. https://doi.org/10.3389/fpsyg.2023.1250051 DOI: https://doi.org/10.3389/fpsyg.2023.1250051
  12. Ecker, U. K., Lewandowsky, S., Cook, J., Schmid, P., Fazio, L. K., Brashier, N., ... & Amazeen, M. A. (2022). The psychological drivers of misinformation belief and its resistance to correction. Nature Reviews Psychology, 1(1), 13-29. https://doi.org/10.1038/s44159-021-00006-y DOI: https://doi.org/10.1038/s44159-021-00006-y
  13. European Parliament, Brussels (2026). Flash Eurobarometer 3592 (Social Media Survey 2025) (ZA9078; Version 1.0.0) [Data set]. GESIS, Cologne. https://doi.org/10.4232/1.14703
  14. Falgoust, G., Winterlind, E., Moon, P., Parker, A., Zinzow, H., & Madathil, K. C. (2022). Applying the uses and gratifications theory to identify motivational factors behind young adult's participation in viral social media challenges on TikTok. Human Factors in Healthcare, 2. https://doi.org/10.1016/j.hfh.2022.100014 DOI: https://doi.org/10.1016/j.hfh.2022.100014
  15. Fletcher, R., & Nielsen, R. K. (2018). Are people incidentally exposed to news on social media? A comparative analysis. New Media & Society, 20(7), 2450-2468. https://doi.org/10.1177/1461444817724170 DOI: https://doi.org/10.1177/1461444817724170
  16. Fletcher, R., Cornia, A., & Nielsen, R. K. (2020). How polarized are online and offline news audiences? A comparative analysis of twelve countries. The international journal of press/politics, 25(2), 169-195. https://doi.org/10.1177/1940161219892768 DOI: https://doi.org/10.1177/1940161219892768
  17. Given, L. M., Case, D. O., & Willson, R. (2023). Looking for information: Examining research on how people engage with information. Emerald Publishing Limited. DOI: https://doi.org/10.1108/S2055-5377202315
  18. Guo, J., & Chen, H. T. (2022). How does multi-platform social media use lead to biased news engagement? Examining the role of counter-attitudinal incidental exposure, cognitive elaboration, and network homogeneity. Social Media+ Society, 8(4). https://doi.org/10.1177/20563051221129140 DOI: https://doi.org/10.1177/20563051221129140
  19. Guo, Z., Schlichtkrull, M., & Vlachos, A. (2022). A survey on automated fact-checking. Transactions of the association for computational linguistics, 10, 178-206. https://doi.org/10.1162/tacl_a_00454 DOI: https://doi.org/10.1162/tacl_a_00454
  20. Hameleers, M. (2022). Populist disinformation: Are citizens with populist attitudes affected most by radical right-wing disinformation?. Media and Communication, 10(4), 129-140. https://doi.org/10.17645/mac.v10i4.5654 DOI: https://doi.org/10.17645/mac.v10i4.5654
  21. Helberger, N., Van Drunen, M., Moeller, J., Vrijenhoek, S., & Eskens, S. (2022). Towards a normative perspective on journalistic AI: Embracing the messy reality of normative ideals. Digital Journalism, 10(10), 1605-1626. https://doi.org/10.1080/21670811.2022.2152195 DOI: https://doi.org/10.1080/21670811.2022.2152195
  22. Jędrzejewski, S., Kuźmicz, K., & Rae, G. (2024). The COVID-19 Pandemic in the Polish and British Media: A Content Analysis. In Risk and Crisis Communication in Europe (pp. 260-275). Routledge. DOI: https://doi.org/10.4324/9781003375296-18
  23. Johansson, E., & Nożewski, J. (2018). Polish and Swedish journalist-politician Twitter networks: Who are the gatekeepers?. Central European Journal of Communication, 11(2). https://doi.org/10.19195/1899-5101.11.2(21).2 DOI: https://doi.org/10.19195/1899-5101.11.2(21).2
  24. Kartal, M., & Tyran, J. R. (2022). Fake news, voter overconfidence, and the quality of democratic choice. American Economic Review, 112(10), 3367-3397. https://doi.org/10.1257/aer.20201844 DOI: https://doi.org/10.1257/aer.20201844
  25. Kim, S., Kim, K., & Xue, H. (2024). Fingerprints of conspiracy theories: Identifying signature information sources of a misleading narrative and their roles in shaping message content and dissemination. Journal of Online Trust and Safety, 2(2). https://doi.org/10.54501/jots.v2i2.152 DOI: https://doi.org/10.54501/jots.v2i2.152
  26. Klinger, U., & Svensson, J. (2015). The emergence of network media logic in political communication: A theoretical approach. New media & society, 17(8), 1241-1257. https://doi.org/10.1177/1461444814522952 DOI: https://doi.org/10.1177/1461444814522952
  27. Klinger, U., & Svensson, J. (2018). The end of media logics? On algorithms and agency. New media & society, 20(12), 4653-4670. https://doi.org/10.1177/1461444818779750 DOI: https://doi.org/10.1177/1461444818779750
  28. Koetke, J., Schumann, K., Bowes, S. M., & Vaupotič, N. (2025). The effect of seeing scientists as intellectually humble on trust in scientists and their research. Nature Human Behaviour, 9(2), 331-344. https://doi.org/10.1038/s41562-024-02060-x DOI: https://doi.org/10.1038/s41562-024-02060-x
  29. Li, X., Liu, Y., Yao, M. (2016). Openness, Activness, and Diversity of Information Exchange in the Context of Online Networks. In: Emerging Media. Uses and Dynamics, New York, Routledge.
  30. Lyons, B. A. (2023). Older Americans are more vulnerable to prior exposure effects in news evaluation. Harvard Kennedy School Misinformation Review. https://doi.org/https://doi.org/10.37016/mr-2020-118 DOI: https://doi.org/10.37016/mr-2020-118
  31. Mishchuk, H., Samoliuk, N., Krol, V., & Rącka, I. (2025). Digital competences of university graduates: Implications for career success. Human Technology, 21(2), 274–292. https://doi.org/10.14254/1795-6889.2025.21-2.2
  32. Motta, M., & Stecula, D. (2023). The effects of partisan media in the face of global pandemic: How news shaped COVID-19 vaccine hesitancy. Political Communication, 40(5), 505-526. https://doi.org/10.1080/10584609.2023.2187496 DOI: https://doi.org/10.1080/10584609.2023.2187496
  33. Nanz, A., & Matthes, J. (2025). Feeling informed or being informed about politics? Effects of first-and second-level incidental exposure on political surveillance knowledge and internal political efficacy. Information, Communication & Society, 28(15), 2702-2719. https://doi.org/10.1080/1369118X.2025.2472945 DOI: https://doi.org/10.1080/1369118X.2025.2472945
  34. Pennycook, G., & Rand, D. G. (2021). The psychology of fake news. Trends in cognitive sciences, 25(5), 388-402. https://doi.org/10.1016/j.tics.2021.02.007 DOI: https://doi.org/10.1016/j.tics.2021.02.007
  35. Pérez-Escolar, M., Lilleker, D., & Tapia-Frade, A. (2023). A systematic literature review of the phenomenon of disinformation and misinformation. Media and communication, 11(2), 76-87. https://doi.org/10.17645/mac.v11i2.6453 DOI: https://doi.org/10.17645/mac.v11i2.6453
  36. Recuero, R. (2025). A systemic framework for disinformation on social media platforms. Platforms & Society, 2. https://doi.org/10.1177/2976862425136719 DOI: https://doi.org/10.1177/29768624251367199
  37. Schaetz, N., Gagrčin, E., Toth, R., & Emmer, M. (2025). Algorithm dependency in platformized news use. New media & society, 27(3), 1360-1377. https://doi.org/10.1177/14614448231193093 DOI: https://doi.org/10.1177/14614448231193093
  38. Schäfer, S. (2023). Incidental news exposure in a digital media environment: a scoping review of recent research. Annals of the International Communication Association, 47(2), 242-260, https://doi.org/10.1080/23808985.2023.2169953 DOI: https://doi.org/10.1080/23808985.2023.2169953
  39. Schinello, S. (2025). Challenges and opportunities in the use of artificial intelligence in creative economy: Insights from expert interviews. Economics and Sociology, 18(1), 199-216. https://doi.org/10.14254/2071-789X.2025/18-1/10 DOI: https://doi.org/10.14254/2071-789X.2025/18-1/10
  40. Shao, C., Hui, P. M., Wang, L., Jiang, X., Flammini, A., Menczer, F., & Ciampaglia, G. L. (2018). Anatomy of an online misinformation network. PloS one, 13(4). https://doi.org/10.1371/journal.pone.0196087 DOI: https://doi.org/10.1371/journal.pone.0196087
  41. Skovsgaard, M., & Andersen, K. (2020). Conceptualizing news avoidance: Towards a shared understanding of different causes and potential solutions. Journalism studies, 21(4), 459-476. https://doi.org/10.1080/1461670X.2019.1686410 DOI: https://doi.org/10.1080/1461670X.2019.1686410
  42. Stefanova, D., Bacheva, K., & Vasilev, V. (2025, June). Conceptual Convergence: Disinformation, Fake News, and Information Influence as a Triad of Security Threats in the Context of Society 5.0. In Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference (Vol. 5, pp. 291-296). https://doi.org/10.17770/etr2025vol5.8470 DOI: https://doi.org/10.17770/etr2025vol5.8470
  43. Tsang, S. J. (2026). Misinformation, disinformation, and fake news? Proposing a typology framework of false information. Journalism, 27(3), 719-739. https://doi.org/10.1177/14648849241304380 DOI: https://doi.org/10.1177/14648849241304380
  44. Tunney, C., Thorson, E., & Chen, W. (2021). Following and avoiding fear-inducing news topics: Fear intensity, perceived news topic importance, self-efficacy, and news overload. Journalism Studies, 22(5), 614-632. https://doi.org/10.1080/1461670X.2021.1890636 DOI: https://doi.org/10.1080/1461670X.2021.1890636
  45. Usman, B., Eric Msughter, A., & Olaitan Ridwanullah, A. (2022). Social media literacy: fake news consumption and perception of COVID-19 in Nigeria. Cogent Arts & Humanities, 9(1). https://doi.org/10.1080/23311983.2022.2138011 DOI: https://doi.org/10.1080/23311983.2022.2138011
  46. Waddell, T. F. (2018). What does the crowd think? How online comments and popularity metrics affect news credibility and issue importance. New Media & Society, 20(8), 3068-3083. https://doi.org/10.1177/1461444817742905 DOI: https://doi.org/10.1177/1461444817742905
  47. Wimmer, L. (2025). Why Disinformation, Fake News, and Conspiracy Theories are not Fiction: A View From Philosophical Aesthetics and Literary Studies. Review of Philosophy and Psychology, 1-17. https://doi.org/10.1007/s13164-025-00775-y DOI: https://doi.org/10.1007/s13164-025-00775-y

How to Cite

Mishchuk, H., Kuźmicz, K., Krol, V., Nożewski, J., & Imreh-Tóth, M. (2026). Media influence and user behaviour in the news environment: Traditional versus social media. Human Technology, 22(1), 219–238. https://doi.org/10.14254/1795-6889.2026.22-1.11