Keywords
Noticias falsas, detección de falsificaciones, estudios de comunicación computacional, modelo conceptual, brecha conceptual, epistemología
Abstract
La detección de noticias falsas se ha convertido en un objetivo de suma importancia tanto en los estudios académicos como en la práctica editorial, creando un área de investigación que comprende la desacreditación periodística de falsificaciones, proyectos interdisciplinarios de verificación de hechos y esfuerzos automatizados de detección de noticias falsas. Sin embargo, con el crecimiento de estas industrias, se ha profundizado una brecha epistemológica entre los estudios «tradicionales» (conceptuales, cualitativos, cuantitativos o mixtos) y computacionales para detectar falsificaciones. Describimos las dos lógicas divergentes de definición y detección falsas. En particular, la regulación internacional, la detección de falsificaciones industriales y la mayoría de los estudios de medios legitiman la «frontera borrosa» entre los hechos y la interpretación, advirtiendo contra la eliminación demasiado estricta de las falsificaciones y preservando la libertad de expresión. Los métodos computacionales, a su vez, son mejores en la detección automática de falsificaciones, pero están orientados al «sí/no», ignorando a menudo la variedad de formas interpretativas en la comunicación pública. Arraigada más profundamente que solo en diseños de investigación individuales, la divergencia de lógicas se agudiza cuando la necesidad pública de una detección falsa clara se encuentra con la libertad de interpretación que resulta de siglos de lucha por los estándares en el discurso público y el periodismo. Empleando una revisión crítica de 45 escritos conceptuales académicos e industriales, describimos las principales deficiencias de la falta de marcadores textuales claros para las noticias falsas en los estudios de medios «tradicionales», por un lado, y de la lógica «sí/no» en la detección computacional de noticias falsas, por el otro. Proponemos un marco epistemológico de cinco pilares para la detección falsa, que incluye verdadero/ falso, hecho/interpretación, discrepancia/solidez, evidencia generada por los medios/usuarios y dimensiones de autoría humana/IA.
References
Al-Rawi, A. (2019). Gatekeeping Fake News Discourses on Mainstream Media Versus Social Media. Social Science Computer Review, 37(6), 687-704. https://doi.org/10.1177/0894439318795849
Albright, J. (2017). Welcome to the era of fake news. Media and Communication, 5(2), 87-89. https://doi.org/10.17645/mac.v5i2.977
Baade, B. (2018). Fake News and International Law. European Journal of International Law, 29(4), 1357-1376. https://doi.org/10.1093/ejil/chy071
Berghel, H. (2017). Lies, Damn Lies, and Fake News. Computer, 50(2), 80-85. https://doi.org/10.1109/MC.2017.56
Bodrunova, S. S. (2020). The Boundaries of Context: Contextual Knowledge in Research on Networked Discussions. In A. Antonyuk & N. Basov (Eds.), Networks in the Global World V (pp. 165-179). Springer International Publishing. https://doi.org/10.1007/978-3-030-64877-0_11
Bodrunova, S. S., & Nepiyushchikh, D. (2019). Unhealthy communication on health: Discursive and ecosystemic features of opinion cumulation in the anti-vaccination discourse on Russian Telegram1. World of Media, (1), 75-108. https://doi.org/10.30547/worldofmedia.1.2024.4
boyd, d., & Crawford, K. (2012). Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon. Information, Communication & Society, 15(5), 662-679. https://doi.org/10.1080/1369118X.2012.678878
Caswell, D. (2019). Structured Journalism and the Semantic Units of News. Digital Journalism, 7(8), 1134-1156. https://doi.org/10.1080/21670811.2019.1651665
Graves, L. (2018). Boundaries Not Drawn: Mapping the institutional roots of the global fact-checking movement. Journalism Studies, 19(5), 613-631. https://doi.org/10.1080/1461670X.2016.1196602
Hilbert, M., Barnett, G., Blumenstock, J., Contractor, N., Diesner, J., Frey, S., González-Bailón, S., et al. (2019). Computational Communication Science: A Methodological Catalyzer for a Maturing Discipline. International Journal of Communication (IJoC), 13, 3912-3934. https://bit.ly/4nRfRyR
Humprecht, E. (2020). How Do They Debunk “Fake News”? A Cross-National Comparison of Transparency in Fact Checks. Digital Journalism, 8(3), 310-327. https://doi.org/10.1080/21670811.2019.1691031
Jaakkola, E. (2020). Designing conceptual articles: four approaches. AMS Review, 10(1), 18-26. https://doi.org/10.1007/s13162-020-00161-0
Kapantai, E., Christopoulou, A., Berberidis, C., & Peristeras, V. (2021). A systematic literature review on disinformation: Toward a unified taxonomical framework. New Media & Society, 23(5), 1301-1326. https://doi.org/10.1177/1461444820959296
Khan, A., Brohman, K., & Addas, S. (2022). The anatomy of ‘fake news’: Studying false messages as digital objects. Journal of Information Technology, 37(2), 122-143. https://doi.org/10.1177/02683962211037693
Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., et al. (2018). The Science of Fake News. Science, 359(6380), 1094-1096. https://doi.org/10.1126/science.aao2998
Lien, C. H., Lee, J., & Tandoc Jr, E. C. (2022). Facing Fakes: Understanding Tech Platforms’ Responses to Online Falsehoods. Digital Journalism, 10(5), 761-780. https://doi.org/10.1080/21670811.2021.1982398
Lim, C. (2018). Checking how fact-checkers check. Research & Politics, 5(3), 2053168018786848. https://doi.org/10.1177/2053168018786848
Mitra, T., & Gilbert, E. (2021). CREDBANK: A Large-Scale Social Media Corpus With Associated Credibility Annotations. Proceedings of the International AAAI Conference on Web and Social Media, 9(1), 258-267. https://doi.org/10.1609/icwsm.v9i1.14625
Molina, M. D., Sundar, S. S., Le, T., & Lee, D. (2021). “Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content. American Behavioral Scientist, 65(2), 180-212. https://doi.org/10.1177/0002764219878224
Morris, K., & Yeoman, F. (2023). Teaching Future Journalists the News: The Role of Journalism Educators in the News Literacy Movement. Journalism Practice, 17(7), 1573-1590. https://doi.org/10.1080/17512786.2021.1992599
Mould, T. (2018). Introduction to the Special Issue on Fake News: Definitions and Approaches. Journal of American Folklore, 131(522), 371-378. https://doi.org/10.5406/jamerfolk.131.522.0371
Nakashole, N., & Mitchell, T. (2014). Language-Aware Truth Assessment of Fact Candidates. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 1009-1019). Association for Computational Linguistics. https://doi.org/10.3115/v1/P14-1095
Neuman, S. (2014, February 14). 1 In 4 Americans thinks the Sun goes around the Earth, survey says. NPR. https://bit.ly/3WM7VnA
Nielsen, R. K., & Graves, L. (2017, October). “News you don’t believe”: Audience perspectives on fake news. Reuters Institute for the Study of Journalism: Factsheet. https://reutersinstitute.politics.ox.ac.uk/our-research/news-you-dont-believe-audience-perspectives-fake-news
Opdahl, A. L., Tessem, B., Dang-Nguyen, D.-T., Motta, E., Setty, V., Throndsen, E., Tverberg, A., et al. (2023). Trustworthy journalism through AI. Data & Knowledge Engineering, 146, 102182. https://doi.org/10.1016/j.datak.2023.102182
Pasquetto, I. V., Swire-Thompson, B., Amazeen, M. A., Benevenuto, F., Brashier, N. M., Bond, R. M., Bozarth, L. C., et al. (2020). Tackling misinformation: What researchers could do with social media data. Harvard Kennedy School Misinformation Review, 1(8), 1-14. https://bit.ly/49JZnFh
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
Porshnev, A., Miltsov, A., Lokot, T., & Koltsova, O. (2021). Effects of Conspiracy Thinking Style, Framing and Political Interest on Accuracy of Fake News Recognition by Social Media Users: Evidence from Russia, Kazakhstan and Ukraine. In G. Meiselwitz (Ed.), Social Computing and Social Media: Experience Design and Social Network Analysis (pp. 341-357). Springer International Publishing. https://doi.org/10.1007/978-3-030-77626-8_23
Reese, S. D. (2023). Writing the Conceptual Article: A Practical Guide. Digital Journalism, 11(7), 1195-1210. https://doi.org/10.1 080/21670811.2021.2009353
Rubin, V. L., Chen, Y., & Conroy, N. K. (2015). Deception detection for news: Three types of fakes. Proceedings of the Association for Information Science and Technology, 52(1), 1-4. https://doi.org/10.1002/pra2.2015.145052010083
Saldaña, M., & Vu, H. T. (2022). You Are Fake News! Factors Impacting Journalists’ Debunking Behaviors on Social Media. Digital Journalism, 10(5), 823-842. https://doi.org/10.1080/21670811.2021.2004554
Schapals, A. K. (2018). Fake News. Journalism Practice, 12(8), 976-985. https://doi.org/10.1080/17512786.2018.1511822
Scott, C. P. (1921, May 5). A hundred years. The Manchester Guardian. https://clck.ru/3QDZ49
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. https://doi.org/10.1145/3137597.3137600
Silverman, C., Strapagiel, L., Shaban, H., Hall, E., & Singer-Vine, J. (2016, October 20). Hyperpartisan Facebook Pages Are Publishing False And Misleading Information At An Alarming Rate. Buzzfeed.News. https://clck.ru/3QDYu7
Simons, G., & Manoilo, A. (2021). The what, how and why of fake news: An overview. World of Media. Journal of Russian Media and Journalism Studies, 2, 35-55. https://doi.org/10.30547/worldofmedia.2.2021.2
Strasser, B. J. (2012). Data-driven sciences: From wonder cabinets to electronic databases. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 43(1), 85-87. https://doi.org/10.1016/j.shpsc.2011.10.009
Tandoc Jr, E. C., Lim, Z. W., & Ling, R. (2018a). Defining “Fake News”. Digital Journalism, 6(2), 137-153. https://doi.org/10.1 080/21670811.2017.1360143
Tandoc Jr, E. C., Ling, R., Westlund, O., Duffy, A., Goh, D., & Zheng Wei, L. (2018b). Audiences’ acts of authentication in the age of fake news: A conceptual framework. New Media & Society, 20(8), 2745-2763. https://doi.org/10.1177/1461444817731756
Tricco, A. C., Lillie, E., Zarin, W., O’Brien, K. K., Colquhoun, H., Levac, D., Moher, D., et al. (2018). PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Annals of Internal Medicine, 169(7), 467-473. https://doi.org/10.7326/M18-0850
Tully, M. (2022). Everyday News Use and Misinformation in Kenya. Digital Journalism, 10(1), 109-127. https://doi.org/10.1080/21670811.2021.1912625
Tully, M., Madrid-Morales, D., Wasserman, H., Gondwe, G., & Ireri, K. (2022). Who is Responsible for Stopping the Spread of Misinformation? Examining Audience Perceptions of Responsibilities and Responses in Six Sub-Saharan African Countries. Digital Journalism, 10(5), 679-697. https://doi.org/10.1080/21670811.2021.1965491
Tumber, H., & Waisbord, S. R. (2021). The Routledge Companion to Media Disinformation and Populism. Routledge. https://doi.org/10.4324/9781003004431
van Atteveldt, W., & Peng, T.-Q. (2018). When Communication Meets Computation: Opportunities, Challenges, and Pitfalls in Computational Communication Science. Communication Methods and Measures, 12(2-3), 81-92. https://doi.org/10.1080/1 9312458.2018.1458084
Vartanova, E., & Lukina, M. (2022). The Triple Typology of Divide: Russia’s Journalism Education in the Times of the COVID-19 Pandemic. Journalism & Mass Communication Educator, 77(1), 74-91. https://doi.org/10.1177/10776958211053675
Vishwakarma, D. K., & Jain, C. (2020). Recent State-of-the-art of Fake News Detection: A Review. In 2020 international conference for emerging technology (INCET) (pp. 1-6). IEEE. https://doi.org/10.1109/INCET49848.2020.9153985
Wagner, M. C., & Boczkowski, P. J. (2019). The Reception of Fake News: The Interpretations and Practices That Shape the Consumption of Perceived Misinformation. Digital Journalism, 7(7), 870-885. https://doi.org/10.1080/21670811.2019.1653208
Waisbord, S. (2018). Truth is What Happens to News. Journalism Studies, 19(13), 1866-1878. https://doi.org/10.1080/146167 0X.2018.1492881
Wang, W. Y. (2017). “Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (pp. 422-426). Association for Computational Linguistics. https://doi.org/10.18653/v1/P17-2067
Wardle, C., & Derakhshan, H. (2017). Information Disorder: Toward an Interdisciplinary Framework for Research and Policymaking (Council of Europe report DGI (2017) 09). Council of Europe. http://bit.ly/47w7Kmp
Zhang, X., & Ghorbani, A. A. (2020). An overview of online fake news: Characterization, detection, and discussion. Information Processing & Management, 57(2), 102025. https://doi.org/10.1016/j.ipm.2019.03.004
Zhou, X., & Zafarani, R. (2018). A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities. arXiv preprint arXiv:1812.00315. https://doi.org/10.48550/arXiv.1812.00315
Fundref
This research is supported in full by Russian Science Foundation, project 25-18-00991 (2025 – 2027), year 1.
Technical information
Received: 2025-08-18 | Reviewed: 2025-10-31 | Accepted: 2025-11-02 | Online First: 2026-04-11 | Published: 2026-04-15
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Svetlana Bodrunova. (2026). La brecha: Lógicas «tradicionales» y computacionales en la detección de noticias falsas. Comunicar, 34(85). 10.5281/zenodo.19690365