“Todo parece veraz”. Credibilidad de la desinformación producida usando IA desde la perspectiva de los estudiantes de comunicación en España

David García-Marín; Rebeca Suárez-Álvarez; Antonio García-Jiménez

doi:10.26441/RC24.2-2025-3872

Autores/as

David García-Marín Universidad Rey Juan Carlos (España) https://orcid.org/0000-0002-4575-1911
Rebeca Suárez-Álvarez Universidad Rey Juan Carlos (España) https://orcid.org/0000-0002-0102-4472
Antonio García-Jiménez Universidad Rey Juan Carlos (España) https://orcid.org/0000-0002-8423-9486

DOI:

https://doi.org/10.26441/RC24.2-2025-3872

Palabras clave:

periodismo, inteligencia artificial, noticias falsas, jóvenes, credibilidad, desinformación, ChatGPT

Resumen

Propósito. El periodismo está viviendo una revolución tecnológica que está modificando sus procesos de producción de noticias y flujos de trabajo. Estas transformaciones se producen en paralelo al cambio de paradigma de los modos de consumo de noticias y al crecimiento de la aplicación de la Inteligencia Artificial (IA). Enmarcada en los estudios sobre la credibilidad percibida de las noticias y en la Teoría de la Disonancia Cognitiva, esta investigación cuestiona si los estudiantes universitarios del área de comunicación, futuros profesionales en este campo son capaces de distinguir las noticias falsas creadas con IA y las verdaderas elaboradas por humanos. Metodología. Se realizó un estudio mediante cuestionario para medir el grado de veracidad, precisión, claridad y, por tanto, credibilidad, de un total de seis noticias tanto falsas creadas utilizando ChatGPT como verdaderas que abordan temáticas de salud, migración y medioambiente. Resultados y conclusiones. Se observó que los participantes no diferencian las noticias falsas creadas con IA de las verdaderas elaboradas por humanos, en términos de veracidad, precisión, claridad y credibilidad. Asimismo, las noticias falsas fueron percibidas como más veraces, precisas y claras, incluso superando a las verdaderas en las tres variables. Aporte original. Se evidencia, por tanto, que el volumen y velocidad en el procesamiento de datos propio de la IA en combinación con la supervisión y conocimiento humanos multiplican las posibilidades de producir contenidos desinformativos con un potencial manipulador desconocidos hasta el momento.

Métricas

Cargando métricas ...

Biografía del autor/a

David García-Marín, Universidad Rey Juan Carlos (España)

Doctor en Sociología y Medios de Comunicación por la Universidad Nacional de Educación a Distancia (UNED, España). Profesor Titular en la Universidad Rey Juan Carlos. Autor de un centenar de publicaciones centradas en la desinformación, el fact-checking y la inteligencia artificial aplicada a la comunicación. Miembro del Grupo de Expertos contra la Desinformación del Departamento de Seguridad Nacional de España. https://orcid.org/0000-0002-4575-1911, david.garciam@urjc.es

Rebeca Suárez-Álvarez, Universidad Rey Juan Carlos (España)

Profesora Titular de la Universidad Rey Juan Carlos. Miembro del grupo de investigación Comunicación, Sociedad y Cultura (GICOMSOC). Sus principales líneas de investigación son redes sociales, periodismo, audiencias digitales y menores. Investigadora en los proyectos ''Repertorios y prácticas mediáticas en la adolescencia y la juventud: usos, cibersalud y vulnerabilidades digitales en las redes sociales'' y Erasmus+ “SchoolFaN project (Schools against fake news for a cooler future)”. https://orcid.org/0000-0002-0102-4472, rebeca.suarez@urjc.es

Antonio García-Jiménez, Universidad Rey Juan Carlos (España)

Catedrático de Periodismo en la Universidad Rey Juan Carlos, investigador principal de Grupo de Investigación en Comunicación, Sociedad y Cultura (GICOMSOC), dirige un proyecto nacional y codirige un proyecto Erasmus+. Su investigación está vinculada a la tecnología y sus usos en el ámbito de los estudios de comunicación -con especial énfasis en los menores y los jóvenes-, la desinformación, las características de las noticias en redes sociales, y el comportamiento sexualizante de los adolescentes en este contexto. nhttps://orcid.org/0000-0002-8423-9486, antonio.garcia@urjc.es

Citas

Aghion, P., Benjamin F. J., & Jones, Charles I. (2019). Artificial Intelligence and Economic Growth. In A. Agrawal, J. Gans, & A. Goldfarb (Eds.), The Economics of Artificial Intelligence: An Agenda (pp. 237-290). The University of Chicago Press DOI: https://doi.org/10.7208/chicago/9780226613475.003.0009

Bárrig, P., & Alarcón, D. (2017). Temperamento y competencia social en niños y niñas preescolares de San Juan de Lurigancho: un estudio preliminar. Liberabit, 23, 5-88. https://doi.org/10.24265/liberabit.2017.v23n1.05 DOI: https://doi.org/10.24265/liberabit.2017.v23n1.05

Bastian, M., Helberger, N., & Makhortykh, M. (2021). Safeguarding the journalistic DNA: Attitudes towards the role of professional values in algorithmic news recommender designs. Digital Journalism, 9(6), 835-863. https://doi.org/10.1080/21670811.2021.1912622 DOI: https://doi.org/10.1080/21670811.2021.1912622

Baum, S. D. (2020). Social choice ethics in artificial intelligence. Ai & Society, 35(1), 165-176. https://doi.org/10.1007/s00146-017-0760-1 DOI: https://doi.org/10.1007/s00146-017-0760-1

Bernard, S. (2024). Investigating curriculum integrated information literacy. The Journal of Academic Librarianship, 50(1), 102839. https://doi.org/10.1016/j.acalib.2023.102839 DOI: https://doi.org/10.1016/j.acalib.2023.102839

Borel, B. (2023). The Chicago guide to fact-checking. University of Chicago Press. DOI: https://doi.org/10.7208/chicago/9780226817903.001.0001

Breakstone, J., Smith, M., Connors, P., Ortega, T., Kerr, D., & Wineburg, S. (2021). Lateral reading: College students learn to critically evaluate internet sources in an online course. The Harvard Kennedy School Misinformation Review. https://doi.org/10.37016/mr-2020-56 DOI: https://doi.org/10.37016/mr-2020-56

Bridgman, A., Merkley, E., Loewen, P. J., Owen, T., Ruths, D., Teichmann, L., & Zhilin, O. (2020). The causes and consequences of COVID-19 misperceptions: Understanding the role of news and social media. Harvard Kennedy School Misinformation Review, 1(3). https://doi.org/10.37016/mr-2020-028 DOI: https://doi.org/10.37016/mr-2020-028

Catalina-García, B., Sousa, J., & Cristina Silva Sousa, L.-C. S. (2019). Consumo de noticias y percepción de fake news entre estudiantes de Comunicación de Brasil, España y Portugal. Revista De Comunicación, 18(2). https://doi.org/10.26441/RC18.2-2019-A5 DOI: https://doi.org/10.26441/RC18.2-2019-A5

Canavilhas, J. (2022). Artificial intelligence and journalism: Current situation and expectations in the Portuguese sports media. Journalism and Media, 3(3), 510-520. https://doi.org/10.3390/journalmedia3030035 DOI: https://doi.org/10.3390/journalmedia3030035

Canavilhas, J., & Giacomelli, F. (2023). Artificial Intelligence in sports journalism: A study in Brazil and Portugal. Revista de Comunicación, 22(1), 53–69. https://doi.org/10.26441/RC22.1-2023-3005 DOI: https://doi.org/10.26441/RC22.1-2023-3005

Carnahan, D., Ulusoy, E., Barry, R., McGraw, J., Virtue, I., & Bergan, D. E. (2022). What should I believe? A conjoint analysis of the influence of message characteristics on belief in, perceived credibility of, and intent to share political posts. Journal of Communication, 72(5), 592–603. https://doi.org/10.1093/joc/jqac023 DOI: https://doi.org/10.1093/joc/jqac023

Carballo, W., & Marroquín Parducci, A. (2020). Media literacy and news consumption among young Salvadorans in digital times. Alcance, 9(22), 144-155. http://scielo.sld.cu/pdf/ralc/v9n22/2411-9970-ralc-9-22-144.pdf

Civila, S., Castillo-Abdul, B., & Romero-Rodríguez, L.M. (2021). El efecto ventrílocuo en las agencias internacionales de noticias. Revisión teórica e incidencia en las nuevas formas de desinformación. Vivat Academia, 154, 25-46. https://doi.org/10.15178/va.2021.154.e1302 DOI: https://doi.org/10.15178/va.2021.154.e1302

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159. https://doi.org/10.1037/0033-2909.112.1.155 DOI: https://doi.org/10.1037//0033-2909.112.1.155

Corbetta, P. (2007). Metodologías y técnicas de investigación social. Mc Graw Hill/Interamericana de España.

da Silva, J. R. (2023). Connect-the-Dots: Artificial Intelligence and Automation in Investigative Journalism. Faculdade de Engenharia da Universidade do Porto. https://repositorio-aberto.up.pt/bitstream/10216/153970/2/648196.pdf

Del-Fresno-García, M. (2019). Desórdenes informativos: sobreexpuestos e infrainformados en la era de la posverdad. El profesional de la información, 28(3), e280302. https://doi.org/10.3145/epi.2019.may.02 DOI: https://doi.org/10.3145/epi.2019.may.02

Domínguez-Lara S. (2017). Magnitud del efecto en análisis de regresión. Interacciones, 3, 3-5. https://doi.org/10.24016/2017.v3n1.46 DOI: https://doi.org/10.24016/2017.v3n1.46

Du, Y. R., Zhu, L., & Cheng, B. K. L. (2019). Are Numbers Not Trusted in a “Post-Truth” Era? An Experiment on the Impact of Data on News Credibility. Electronic News, 13(4), 179-195. https://doi.org/10.1177/1931243119883839 DOI: https://doi.org/10.1177/1931243119883839

Edelman (2023). Trust Barometer 2023. Navigating a polarized world. https://www.edelman.com/trust/2023/trust-barometer

Erba, J., Ternes, B., Bobkowski, P., Logan, T., & Liu, Y. (2018). Sampling Methods and Sample Populations in Quantitative Mass Communication Research Studies: A 15-Year Census of Six Journals. Communication Research Reports, 35(1), 42–47. https://doi.org/10.1080/08824096.2017.1362632 DOI: https://doi.org/10.1080/08824096.2017.1362632

Fawzi, N., Steindl, N., Obermaier, M., Prochazka, F., Arlt, D., Blöbaum, B., & Ziegele, M. (2021). Concepts, causes and consequences of trust in news media–a literature review and framework. Annals of the International Communication Association, 45(2), 154-174. https://doi.org/10.1080/23808985.2021.1960181 DOI: https://doi.org/10.1080/23808985.2021.1960181

Fernández, C., & García, F. (2016). The use of mobile phones as tool for access and knowledge exchange by students in Spain when studying. Prisma Social, (Especial 1), 190-208. https://revistaprismasocial.es/article/view/1318

Festinger, L. (1957). A Theory of Cognitive Dissonance. Stanford University Press. DOI: https://doi.org/10.1515/9781503620766

Fisher, C., Flew, T., Park, S., Lee, J. Y., & Dulleck, U. (2021). Improving trust in news: Audience solutions. Journalism Practice, 15(10), 1497-1515. https://doi.org/10.1080/17512786.2020.1787859 DOI: https://doi.org/10.1080/17512786.2020.1787859

Flanagin, A. J. & Metzger, M. J. (2000). Perceptions of Internet Information Credibility. Journalism & Mass Communication Quarterly, 77(3), 515–540. https://doi.org/10.1177/107769900007700304 DOI: https://doi.org/10.1177/107769900007700304

Freiling, I., Krause, N. M., Scheufele, D. A., & Brossard, D. (2023). Believing and sharing misinformation, fact-checks, and accurate information on social media: The role of anxiety during COVID-19. New Media & Society, 25(1), 141-162. https://doi.org/10.1177/14614448211011 DOI: https://doi.org/10.1177/14614448211011451

Fuchs, C. (2015). Culture and economy in the age of social media. Routledge. DOI: https://doi.org/10.4324/9781315733517

Galily, Y. (2018). Artificial intelligence and sports journalism: Is it a sweeping change? Technology in society, 54, 47-51. https://doi.org/10.1016/j.techsoc.2018.03.001 DOI: https://doi.org/10.1016/j.techsoc.2018.03.001

García Canclini, N. (2020). Ciudadanos reemplazados por algoritmos. Bielefeld University Press. DOI: https://doi.org/10.1515/9783839448915

García-Jiménez, A., López-de-Ayala López, M. C., & Montes-Vozmediano, M. (2020). Características y percepciones sobre el uso de las plataformas de redes sociales y dispositivos tecnológicos por parte de los adolescentes. ZER Revista de Estudios de Comunicación, 25(48), 269–286. https://doi.org/10.1387/zer.21556 DOI: https://doi.org/10.1387/zer.21556

García-Marín, D. (2021). Las fake news y los periodistas de la generación z. Soluciones post-millennial contra la desinformación. Vivat Academia, 154, 37–63. https://doi.org/10.15178/va.2021.154.e1324 DOI: https://doi.org/10.15178/va.2021.154.e1324

García-Marín, D., & Salvat-Martinrey, G. (2021). Investigación sobre desinformación en España: Análisis de tendencias temáticas a partir de una revisión sistematizada de la literatura. Fonseca, Journal of Communication, 23, 199–225. https://doi.org/10.14201/fjc202123199225 DOI: https://doi.org/10.14201/fjc202123199225

Gaziano, C., & McGrath, K. (1986). Measuring the concept of credibility. Journalism Quarterly, 63, 451–462. https://doi.org/10.1177/107769908606300301 DOI: https://doi.org/10.1177/107769908606300301

Ging, D., & Garvey, S. (2018). ’Written in these scars are the stories I can’t explain’: A content analysis of pro-ana and thinspiration image sharing on Instagram. New Media and Society, 20, 1181–1200. https://doi.org/10.1177/1461444816687288 DOI: https://doi.org/10.1177/1461444816687288

Graefe, A., & Bohlken, N. (2020). Automated journalism: A meta-analysis of readers’ perceptions of human-written in comparison to automated news. Media and Communication, 8(3), 50-59. https://doi.org/10.17645/mac.v8i3.3019 DOI: https://doi.org/10.17645/mac.v8i3.3019

Han, B.C. (2015). La sociedad del cansancio. Herder.

Hernández-Sampieri, R., & Mendoza, C. (2018). Metodología de la investigación. Las rutas cuantitativa, cualitativa y mixta. McGrawHill.

Herrero-Diz, P., Conde-Jiménez, J., Tapia-Frade, A., & Varona-Aramburu, D. (2019). The credibility of online news: an evaluation of the information by university students. Culture and Education, 31(2), 407-435. https://doi.org/10.1080/11356405.2019.1601937 DOI: https://doi.org/10.1080/11356405.2019.1601937

Indriani, S. S., Prasanti, D., & Permana, R. S. M. (2020). Analysis of The Filter Bubble Phenomenon in The Use of Online Media for Millennial Generation (An Ethnography Virtual Study about The Filter Bubble Phenomenon). Nyimak: Journal of Communication, 4(2), 199-209. https://jurnal.umt.ac.id/index.php/nyimak/article/view/2538/1835 DOI: https://doi.org/10.31000/nyimak.v4i2.2538

Kotenidis, E., & Veglis, A. (2021). Algorithmic journalism—Current applications and future perspectives. Journalism and Media, 2(2), 244-257. https://doi.org/10.3390/journalmedia2020014 DOI: https://doi.org/10.3390/journalmedia2020014

Kreps, S., McCain, R. M., & Brundage, M. (2022). All the News That’s Fit to Fabricate: AI-Generated Text as a Tool of Media Misinformation. Journal of Experimental Political Science, 9(1), 104–117. https://doi.org/10.1017/XPS.2020.37 DOI: https://doi.org/10.1017/XPS.2020.37

Liedke, J., & Gottfried, J. (2022). U.S. adults under 30 now trust information from social media almost as much as from national news outlets. Pew Research Center. https://www.pewresearch.org/short-reads/2022/10/27/u-s-adults-under-30-now-trust-information-from-social-media-almost-as-much-as-from-national-news-outlets/

Lippman, W. (1922). Public Opinion. Macmillan.

Lopezosa, C., Codina, L., Pont-Sorribes, C., & Vállez, M. (2023). Use of generative artificial intelligence in the training of journalists: challenges, uses and training proposal. Profesional de la información, 32(4). https://doi.org/10.3145/epi.2023.jul.08 DOI: https://doi.org/10.3145/epi.2023.jul.08

Luca, M., Munger, K., Nagler, J., & Tucker, J. A. (2022). You won’t believe our results! But they might: heterogeneity in beliefs about the accuracy of online media. Journal of Experimental Political Science, 9(2), 267-277. https://doi.org/10.1017/XPS.2020.41 DOI: https://doi.org/10.1017/XPS.2020.41

Marconi, F. (2020). Newsmakers: Artificial intelligence and the future of journalism. Columbia University Press. DOI: https://doi.org/10.7312/marc19136

Marcos Recio, J. C., Sánchez Vigil, J. M., & Olivera Zaldua, M. (2017). La enorme mentira y la gran verdad de la información en tiempos de la postverdad. Scire: representación y organización del conocimiento, 23(2), pp. 13-23. https://ojs.ibersid.eu/index.php/scire/article/view/4446 DOI: https://doi.org/10.54886/scire.v1i2.4446

McCombs, M. (2006). Estableciendo la agenda. El impacto de los medios en la opinión pública y en el conocimiento. Paidós.

McIntyre, L. (2018). Post-Truth. The MIT Press. DOI: https://doi.org/10.7551/mitpress/11483.001.0001

Monsees, L. (2023). Information disorder, fake news and the future of democracy. Globalizations, 20(1), 153-168. https://doi.org/10.1080/14747731.2021.1927470 DOI: https://doi.org/10.1080/14747731.2021.1927470

Moran, R. E., & Shaikh, S. J. (2022). Robots in the news and newsrooms: Unpacking meta-journalistic discourse on the use of artificial intelligence in journalism. Digital journalism, 10(10), 1756-1774. https://doi.org/10.1080/21670811.2022.2085129 DOI: https://doi.org/10.1080/21670811.2022.2085129

Murcia Verdú, F. J., Ramos Antón, R., & Calvo Rubio, L. M. (2022). Comparative analysis of the sports chronicle quality written by artificial intelligence and journalists. Revista Latina de Comunicación Social, 80, 91-111. https://doi.org/10.4185/RLCS-2022-1553 DOI: https://doi.org/10.4185/RLCS-2022-1553

Nasim, S. F., Ali, M. R., & Kulsoom, U. (2022). Artificial intelligence incidents & ethics a narrative review. International Journal of Technology, Innovation and Management, 2(2), 52-64. https://doi.org/10.54489/ijtim.v2i2.80 DOI: https://doi.org/10.54489/ijtim.v2i2.80

Nedelcu, D., & Balaban, D. C. (2021). The Role of Source Credibility and Message Credibility in Fake News Engagement. Perspectives from an Experimental Study. Journal of Media Research, 14(3), 42-62. https://doi.org/10.24193/|mr.41.3 DOI: https://doi.org/10.24193/jmr.41.3

Newman, N. & Fletcher, R. (2017). Bias, Bullshit and Lies: Audience Perspectives on Low Trust in the Media. https://doi.org/10.60625/risj-gf5m-zs14 DOI: https://doi.org/10.2139/ssrn.3173579

Newman, E. J., Jalbert, M. C., Schwarz, N., & Ly, D. P. (2020). Truthiness, the illusory truth effect, and the role of need for cognition. Consciousness and cognition, 78, 102866. https://doi.org/10.1016/j.concog.2019.102866 DOI: https://doi.org/10.1016/j.concog.2019.102866

Nielsen, R. K. & Graves, L. (2017). News You Don’t Believe: Audience Perspectives on Fake News. Oxford: Reuters Institute for the Study of Journalism. https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2017-10/Nielsen%26Graves_factsheet_1710v3_FINAL_download.pdf

Nigro, P. (2018). Causes for the loss of trust in the practices of the press and strategies for its restoration in a context of uncertainty. Hipertext.net, 17, 54-63. https://doi.org/10.31009/hipertext.net.2018.i17.05 DOI: https://doi.org/10.31009/hipertext.net.2018.i17.05

Osho, S. A. (2020). Fake news as aberration in journalism practice: Examining truth and facts as basis of fourth estate of the realm. IntechOpen.

Park, R. (1940). News as a Form of Knowledge: A Chapter in the Sociology of Knowledge. American Journal of Sociology, 45(5), 669-686. http://www.jstor.org/stable/2770043 DOI: https://doi.org/10.1086/218445

Park, S., Fisher, C., Flew, T., & Dulleck, U. (2020). Global mistrust in news: The impact of social media on trust. International Journal on Media Management, 22(2), 83-96. https://doi.org/10.1080/14241277.2020.1799794 DOI: https://doi.org/10.1080/14241277.2020.1799794

Park, M., Sun, Y., & McLaughlin, M.L. (2017). Social media propagation of content promoting risky health behavior. Cyberpsychology Behavavior and Social Network, 20, 278–285. https://doi.org/10.1089/cyber.2016.0698 DOI: https://doi.org/10.1089/cyber.2016.0698

Pastor-Ruiz, Y., Martín-Nieto, R., & Montes-Vozmediano, M. (2019). Patrones de uso, control parental y acceso a la información de los adolescentes en la red. Estudios Sobre El Mensaje Periodístico, 25(2), 995–1012. https://doi.org/10.5209/esmp.64821 DOI: https://doi.org/10.5209/esmp.64821

Pedrero-Esteban, L. M., Rubio-Romero, J., & Jiménez-Narros, C. (2021). Fake News Reaching Young People on Social Networks: Distrust Challenging Media Literacy. Publications, 9(24). https://doi.org/10.3390/publications9020024 DOI: https://doi.org/10.3390/publications9020024

Pérez Escoda, A., & Pedrero Esteban, L.M. (2021). Challenges for journalism facing social networks, fake news, and the distrust of Generation Z. Revista Latina de Comunicación Social, 79, 67-85. https://www.doi.org/10.4185/RLCS-2021-1519ABSTRACT DOI: https://doi.org/10.4185/RLCS-2021-1519

Picazo-Sánchez, L., Domínguez-Martín, R., & García-Marín, D. (2022). Health Promotion on Instagram: Descriptive–Correlational Study and Predictive Factors of Influencers’ Content. International Journal of. Environmental Research and Public Health, 19,15817. https://doi.org/10.3390/ijerph192315817 DOI: https://doi.org/10.3390/ijerph192315817

Shin, D. (2022). The perception of humanness in conversational journalism: An algorithmic information-processing perspective. New Media & Society, 24(12), 2680-2704. https://doi.org/10.1177/146144482199380 DOI: https://doi.org/10.1177/1461444821993801

Smith, R. A. (2014). Testing the Model of Stigma Communication with a Factorial Experiment in an Interpersonal Context. Communication Studies, 65(2), 154–173. https://doi.org/10.1080/10510974.2013.851095 DOI: https://doi.org/10.1080/10510974.2013.851095

Steensen, S., Belair-Gagnon, V., Graves, L., Kalsnes, B., & Westlund, O. (2022). Journalism and source criticism. Revised approaches to assessing truth-claims. Journalism Studies, 23(16), 2119-2137. https://doi.org/10.1080/1461670X.2022.2140446 DOI: https://doi.org/10.1080/1461670X.2022.2140446

Stray, J. (2021). Making Artificial Intelligence Work for Investigative Journalism. Digital Journalism, 7(8), 1076-1097. https://doi.org/10.1080/21670811.2019.1630289 DOI: https://doi.org/10.1080/21670811.2019.1630289

Swart, J. (2023). Tactics of news literacy: How young people access, evaluate, and engage with news on social media. New Media & Society, 25(3), 505-521. https://doi.org/10.1177/146144482110114 DOI: https://doi.org/10.1177/14614448211011447

Túñez-López, J.-M., Toural-Bran, C., & Cacheiro-Requeijo, S. (2018). Automated-content generation using news-writing bots and algorithms: Perceptions and attitudes amongst Spain’s journalists. Profesional de la información, 27(4), 750–758. https://doi.org/10.3145/epi.2018.jul.04 DOI: https://doi.org/10.3145/epi.2018.jul.04

Van Aelst, P., Toth, F., Castro, L., Štětka, V., Vreese, C. D., Aalberg, T., & Theocharis, Y. (2021). Does a crisis change news habits? A comparative study of the effects of COVID-19 on news media use in 17 European countries. Digital Journalism, 9(9), 1208-1238. https://doi.org/10.1080/21670811.2021.1943481 DOI: https://doi.org/10.1080/21670811.2021.1943481

Van Dijck, J. (2016). La cultura de la conectividad. Una historia crítica de las redes sociales. Siglo Veintiuno Editores.

Ventura-León, J. L. (2019). Tamaño del efecto para Kruskal-Wallis: aportes al artículo de Domínguez-González et al. Investigación en educación médica, 30(8), 135-136. https://doi.org/10.1016/j.riem.2017.07.002 DOI: https://doi.org/10.1016/j.riem.2017.07.002

Vizcaíno-Laorga, R., Montes Vozmediano, M., & De La Torre, P. (2017). Tocando la realidad en la producción de contenidos informativos, rutinas profesionales y participación en entornos digitales. Prisma Social, 19, 192-225. https://revistaprismasocial.es/article/view/1481/1662

Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146-1151. https://doi.org/10.1126/science.aap9559 DOI: https://doi.org/10.1126/science.aap9559

Vu, H. T., & Chen, Y. (2024). What Influences Audience Susceptibility to Fake Health News: An Experimental Study Using a Dual Model of Information Processing in Credibility Assessment. Health Communication, 39(6), 1113–1126. https://doi.org/10.1080/10410236.2023.2206177 DOI: https://doi.org/10.1080/10410236.2023.2206177

Wang, B., & Liu, J. (2024). Cognitively Biased Users Interacting with Algorithmically Biased Results in Whole-Session Search on Controversial Topics. Human-Computer Interaction, 227-237. https://doi.org/10.1145/3664190.3672520 DOI: https://doi.org/10.1145/3664190.3672520

Wardle, C., & Derakhshan, H. (2017). Information Disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe report DGI (2017)09. https://tverezo.info/wp-content/uploads/2017/11/PREMS-162317-GBR-2018-Report-desinformation-A4-BAT.pdf

Whittaker, J. P. (2019). Tech Giants, Artificial Intelligence and the Future of Journalism. Taylor & Francis. DOI: https://doi.org/10.4324/9781351013758

Wölker, A., & Powell, T. E. (2021). Algorithms in the newsroom? News readers’ perceived credibility and selection of automated journalism. Journalism, 22(1), 86-103. https://doi.org/10.1177/14648849187570 DOI: https://doi.org/10.1177/1464884918757072

Wu, Y. (2020). Is automated journalistic writing less biased? An experimental test of auto-written and human-written news stories. Journalism Practice, 14(8), 1008-1028. https://doi.org/10.1080/17512786.2019.1682940 DOI: https://doi.org/10.1080/17512786.2019.1682940

Zhao, Y., Zhou, T., & Zhou, Y. (2021). On the Relationship among User’s Reading Behavior, Algorithm Recommendation Mechanism and the Manufactured Filter Bubbles Effect. Converter, 730-744. https://doi.org/10.17762/converter.107Id DOI: https://doi.org/10.17762/converter.107