News consumption profiles facing disinformation: exposure and responses to suspect information
DOI:
https://doi.org/10.31921/doxacom.3519Keywords:
Incidental news consumption, News avoidance, Generative artificial intelligence, social media, fact-checkingAbstract
This article analyses news consumption profiles and their relationship with the suspicion of having encountered false information, as well as the reactions adopted in response to such suspicion. Using data from a representative survey (n = 1,550), three consumption profiles are identified through cluster analysis. Subsequently, logistic regression models are estimated to examine the likelihood of suspecting exposure to disinformation and of responding by cross-checking information in traditional media, consulting fact-cheking sources, or taking no action. The results show that profiles characterised by higher digital consumption display a greater probability of suspicion, but not necessarily a higher likelihood of active responses. Political interest emerges as the main predictor of proactive reactions, while passivity is particularly concentrated among digital profiles with low informational interest. These findings suggest that the management of disinformation is unevenly distributed across the citizenry, disproportionately relying on the most politically engaged sectors, thereby reinforcing inequalities within the digital public sphere.
Downloads
Global Statistics ℹ️
|
0
Views
|
0
Downloads
|
|
0
Total
|
|
References
Anderson, K. J. (2025). What is News? Exploring Differences in How Younger and Older Cohorts Use News in Today's Media Environment. Communication Research and Practice, 11(1), 3-23. https://doi.org/10.1080/22041451.2024.2344997
Boczkowski, P. J., Matassi, M., y Mitchelstein, E. (2017). Incidental News: How Young People Consume News on Social Media. Proceedings of the 50th Hawaii International Conference on System Sciences, 1785-1792. https://hdl.handle.net/10125/41371
Bode, L. (2016). Political news in the news feed: Learning politics from social media. Mass Communication & Society, 19(1), 24-48. https://doi.org/10.1080/15205436.2015.1045149
Calinski, T., y Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics-theory and Methods, 3(1), 1-27.
Catalina-García, B., García-Jiménez, A., y Paniagua-Santamaría, P. (2021). Percepción del consumo de noticias en línea y de las prácticas relacionadas a ellas por parte de los jóvenes de la Comunidad de Madrid (España). Cuadernos.info, (50), 22-44. https://doi.org/10.7764/cdi.50.27513
Ceballos-del-Cid, Y., Gómez-Calderón, B., y Córdoba-Cabús, A. (2025). Redes sociales y hábitos de consumo informativo de los jóvenes españoles: un análisis diacrónico (2021-2023) [Social Media and News Consumption among Young Spaniards: A Diachronic Analysis (2021-2023)]. Revista Mediterránea de Comunicación/Mediterranean Journal of Communication, 16(1), e28010. https://www.doi.org/10.14198/MEDCOM.28010
Comisión Europea (2018). La lucha contra la desinformación en línea: un enfoque europeo. Comisión Europea, Bruselas. https://eur-lex.europa.eu/legal-content/ES/TXT/?uri=CELEX:52018DC0236
Dubois, E., & Blank, G. (2018). The echo chamber is overstated: the moderating effect of political interest and diverse media. Information, Communication & Society, 21(5), 729–745. https://doi.org/10.1080/1369118X.2018.1428656
Feridouni Solimani, A., y Ahmed-Mohamed, K. (2024). Ciudadanía Digital: Niveles, Consumo y Confianza en la Información de los Jóvenes Españoles. Media & Jornalismo, 45(9), 1-21. https://doi.org/10.14195/2183-5462_45_9
Fernández-Torres, M.J. y Cea, N. (2025): "Europa ante el desafío de la desinformación en tiempos de inteligencia artificial”. En: L. Teruel y L. García Faroldi (Eds). Los medios de comunicación ante la desinformación: inteligencia artificial, discursos de odio, teorías de la conspiración y verificación". Tirant lo Blanch, pp. 363-380. https://riuma.uma.es/xmlui/handle/10630/39110
Fletcher, R., y Park, S. (2017). The impact of trust in the news media on online news consumption and participation. Digital Journalism, 5(10), 1281–1299. https://doi.org/10.1080/21670811.2017.1279979
Hair, J. F., Black, W. C., Babin, B. J., y Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
Haller, A., y Holt, K. (2019). Paradoxical populism: How PEGIDA relates to mainstream and alternative media. Information, Communication & Society, 22(12), 1665–1680
Hameleers, M., Brosius, A., y de Vreese, C. H. (2022a). Whom to trust? Media exposure patterns of citizens with perceptions of misinformation and disinformation related to the news media. European Journal of Communication, 37(3), 237–268. https://doi.org/10.1177/02673231211072667
Hudders, L., De Jans, S., y De Veirman, M. (2020). The commercialization of social media stars: A literature review and conceptual framework on the strategic use of social media influencers. International Journal of Advertising, 40(3), 327–375. https://doi.org/10.1080/02650487.2020.1836925
Katz, E. (1957). The two‐step flow of communication: An up‐to‐date report on an hypothesis. Public Opinion Quarterly, 21(1), 61–78. https://doi.org/10.1086/266687
Katz, E., Haas, H., y Gurevitch, M. (1973). On the use of the mass media for important things. American Sociological Review, 38(2), 164–181. https://doi.org/10.2307/2094393
Katz, E., Blumler, J. G., y Gurevitch, M. (1974). Utilization of mass communication by the individual. En J. G. Blumler & E. Katz (Eds.), The uses of mass communications: Current perspectives on gratifications research (pp. 19–31). Beverly Hills: Sage.
Lazarsfeld, P. F., Berelson, B., & Gaudet, H. (1944). The people’s choice: How the voter makes up his mind in a presidential campaign. Duell, Sloan and Pearce.
Lowenstein-Barkai, H. y Lev-on, A. (2022) News videos consumption in an age of new media: a comparison between adolescents and adults, Journal of Children and Media, 16:1, 78-94, DOI: 10.1080/17482798.2021.1915831
McQuail, D., Blumler, J. G., y Brown, R. (1972). The television audience: A revised perspective. In D. McQuail (Ed.), Sociology of mass communication. Middlesex: Penguin.
Milligan, G. W., y Cooper, M. C. (1985). An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50(2), 159-179.
Pariser, E. (2011). The filter bubble: How the new personalized web is changing what we read and how we think. London: Penguin.
Park, S., Fisher, C., Flew, T., y Dulleck, U. (2020). Global mistrust in news: The impact of social media on trust. The International Journal on Media Management, 22(2), 83–96. https://doi.org/10.1080/14241277.2020.1799794
Peter, C. y Muth, L. (2023). Social Media Influencers’ Role in Shaping Political Opinions and Actions of Young Audiences. Media and Communication, 11 (3), Pages 164–174. https://doi.org/10.17645/mac.v11i3.6750
Punj, G., y Stewart, D. W. (1983). Cluster analysis in marketing research: Review and suggestions for application. Journal of Marketing Research, 20(2), 134-148.
Rasul, M. E., Calabrese, C., Oh, Y. J., Cho, H. J., Jeon, M., y Boukes, M. (2025). "It's All Fake News!": How Perceptions of Misinformation and Disinformation Influence News Consumption Across Traditional Media, Social Media, and AI. Journalism & Mass Communication Quarterly, 102(4), 993-1019. https://doi.org/10.1177/10776990251373085
Sedano, J., Blanco, S. y Palomo, B. (2025): "Imagen y desinformación en la era de la inteligencia artificial". En: L. Teruel y L. García Faroldi (Eds). Los medios de comunicación ante la desinformación: inteligencia artificial, discursos de odio, teorías de la conspiración y verificación, Tirant lo Blanch, pp. 337-361. https://riuma.uma.es/xmlui/handle/10630/39110
Shao, C., Ciampaglia, G. L., Varol, O., Flammini, A., & Menczer, F. (2017). The spread of fake news by social bots. arXiv preprint arXiv:1707.07592, 96, 104. ArXiv e-prints.
Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsletter, 19(1), 22–36.
Shu, K., Bhattacharjee, A., Alatawi, F., H. Nazer, T.H., Ding, K., Karami, M. y Liu, H. (2020). Combating disinformation in a social media age. WIREs Data Mining Knowl Discov., 10:e1385. https://doi.org/10.1002/widm.1385
Stehr, P., Rössler, P., Leißner, L., & Schönhardt, F. (2015). Parasocial opinion leadership media personalities’ influence within parasocial relations: Theoretical conceptualization and preliminary results. International Journal of Communication, 9, 982–1001. https://doi.org/1932–8036/20150005
Terren, L., & Borge, R. (2021). Echo Chambers on Social Media: A Systematic Review of the Literature. Review of Communication Research, 9, 1–39. https://doi.org/10.12840/ISSN.2255-4165.028
Teruel, L., Blanco, S., Cea Esteruelas, N. y Congosto, M. (2026). Polarización en Twitter/X: análisis del debate generado por los medios de comunicación durante las elecciones locales y autonómicas del 28-M-2023 en España. REDES, Revisa Hispana para el Análisis de Redes Sociales, 36 (2).
Tucker, J. A., Guess, A., Barberá, P., Vaccari, C., Siegel, A., Sanovich, S., Stukal, D., & Nyhan, B. (2018). Social Media, Political Polarization, and Political Disinformation: A Review of the Scientific Literature.
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151.
Ward, J. H., Jr. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301), 236-244.
Wojcieszak, M., Menchen-Trevino, E., Clemm von Hohenberg, B., de Leeuw, S., Gonçalves, J., Davidson, S., y Gonçalves, A. (2024). Non-News Websites Expose People to More Political Content Than News Websites: Evidence from Browsing Data in Three Countries. Political Communication, 41(1), 129–151. https://doi.org/10.1080/10584609.2023.2238641
Zafra Arroyo, A., Sánchez González, M., & Sánchez Gonzales, H. M. (2025). Innovaciones con IA generativa para alfabetización y verificación en la Unión Europea. Doxa Comunicación. Revista Interdisciplinar De Estudios De Comunicación Y Ciencias Sociales, 41, 489-509. https://doi.org/10.31921/doxacom.n41a2874
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Pablo Pastora Estebanez, Livia García Faroldi

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The authors retain their copyright and grant the journal the right of first publication of their work, which will be simultaneously subject to the Creative Commons License, Attribution-NonCommercial, International License (CC BY-NC 4.0). The scientific community is free to share, copy, and redistribute the material in any medium or format, and to remix, transform, and build upon that material under the following terms: Proper credit must be given (journal, authors, URL/DOI), and it is not used for commercial purposes.



















