Algoritmos y comunicaciónRevisión sistematizada de la literatura

  1. Berta García-Orosa 1
  2. João Canavilhas 2
  3. Jorge Vázquez-Herrero 1
  1. 1 Universidade de Santiago de Compostela

    Universidade de Santiago de Compostela

    Santiago de Compostela, España


  2. 2 Universidade da Beira Interior, Covilhã (Portugal)
Comunicar: Revista Científica de Comunicación y Educación

ISSN: 1134-3478

Ano de publicación: 2023

Título do exemplar: Educación para la ciudadanía digital: Algoritmos, automatización y comunicación

Número: 74

Páxinas: 9-21

Tipo: Artigo

DOI: 10.3916/C74-2023-01 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Outras publicacións en: Comunicar: Revista Científica de Comunicación y Educación


The influence of algorithms on society is increasing due to their growing presence in all areas of daily life. Although we are not always aware of it, they sometimes usurp the identity of other social actors. The main purpose of this article is to address the meta-research on the field of artificial intelligence and communication from a holistic perspective that allows us to analyze the state of academic research, as well as the possible effects on these areas and on the democratic system. To this end, we carried out a systematized review of recent literature using quantitative and qualitative approaches. The subject analyzed is changing and novel: it includes the impact and interaction of algorithms, bots, automated processes, and artificial intelligence mechanisms in journalism and communication, as well as their effects on democracy. The results show expanding scientific production, mostly in English, based on theoretical discussion or focused on the perception of communication professionals. The object of study is centered mostly on journalism and democracy, and to a lesser degree on ethics or education. Studies indicate great interest in the effects of the use of algorithms on journalism and democracy, but the answers are still uncertain and the challenges for the coming years are significant.

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Referencias bibliográficas

  • 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.
  • Bimber, B., & Gil-De-Zúñiga, H. (2020). The unedited public sphere. New Media and Society, 22(4), 700-715.
  • Bodó, B. (2019). Selling news to audiences - A qualitative inquiry into the emerging logics of algorithmic news personalization in European quality news media. Digital Journalism, 7(8), 1054-1075.
  • Borges, P.M., & Gambarato, R.R. (2019). The role of beliefs and behavior on Facebook: A semiotic approach to algorithms, fake news, and transmedia journalism. International Journal of Communication, 13, 603-618.
  • Broersma, M., & Harbers, F. (2018). Exploring machine learning to study the long-term transformation of news: Digital newspaper archives, journalism history, and algorithmic transparency. Digital Journalism, 6(9), 1150-1164.
  • Broussard, M., Diakopoulos, N., Guzman, A.L., Abebe, R., Dupagne, M., & Chuan, C.H. (2019). Artificial intelligence and journalism. Journalism and Mass Communication Quarterly, 96(3), 673-695.
  • Bucher, T. (2017). ‘Machines don’t have instincts’: Articulating the computational in journalism. New Media and Society, 19(6), 918-933.
  • Calvo-Rubio, L.M., & Ufarte-Ruiz, M.J. (2020). Perception of teachers, students, innovation managers and journalists about the use of artificial intelligence in journalism. Profesional de la Información, (1), 29-29.
  • Canavilhas, J. (2022). Artificial intelligence in journalism: Automatic translation and recommendation system in the project “A European Perspective” (EBU). Revista Latina de Comunicación Social, 80, 1-13.
  • Canavilhas, J., Satuf, I., Luna, D., Torres, V., Baccin, A., & Marques, A. (2016). Jornalistas e tecnoatores: A negociação de culturas profissionais em redações on-line. Revista Famecos, (3), 23-23.
  • Castells, M. (2022). Digital politics: A paradigm shift. In B. García-Orosa (Ed.), Digital political communication strategies. Multidisciplinary reflections (pp. 5-7). Palgrave.
  • Choi, S. (2019). An exploratory approach to the computational quantification of journalistic values. Online Information Review, 43(1), 133-148.
  • Codina, L. (2018). Revisiones bibliográficas sistematizadas: Procedimientos generales y framework para ciencias humanas y sociales. [Máster dissertation, Universitat Pompeu Fabra].
  • Danzon-Chambaud, S., & Cornia, A. (2021). Changing or reinforcing the “rules of the game”: A field theory perspective on the impacts of automated journalism on media practitioners. Journalism Practice.
  • De-La-Torre, J. (2020). Los periodistas no creen que la Inteligencia Artificial pueda substituirlos. Escudo digital.
  • Diakopoulos, N., Trielli, D., & Lee, G. (2021). Towards understanding and supporting journalistic practices using semi-automated news discovery tools. In J. Nichols (Ed.), Proceedings of the ACM on Human-Computer Interaction (pp. 1-30). Association for Computing Machinery.
  • Dierickx, L. (2021). News automation, materialities, and the remix of an editorial process. Journalism.
  • Dörr, K.N., & Hollnbuchner, K. (2017). Ethical challenges of algorithmic journalism. Digital Journalism, 5(4), 404-419.
  • Dubois, E., & Mckelvey, F. (2019). Political bots: Disrupting Canada’s democracy. Canadian Journal of Communication, 44(2), 27-34.
  • Eldridge, S.A., García-Carretero, L., & Broersma, M. (2019). Disintermediation in social networks: Conceptualizing political actors’ construction of publics on Twitter. Media and Communication, 7, 271-285.
  • Fletcher, R., Schifferes, S., & Thurman, N. (2020). Building the ‘Truthmeter’: Training algorithms to help journalists assess the credibility of social media sources. Convergence, 26(1), 19-34.
  • Ford, H., & Hutchinson, J. (2019). Newsbots that mediate journalist and audience relationships. Digital Journalism, 7(8), 1013-1031.
  • García-Orosa, B. (2018). Perfil de la audiencia de cibermedios: representación discursiva y praxis del receptor 2.0. Palabra Clave, 21, 111-133.
  • García-Orosa, B. (2022). Digital political communication: Hybrid intelligence, algorithms, automation and disinformation in the fourth wave. In B. García-Orosa (Ed.), Digital Political Communication Strategies. Palgrave.
  • García-Orosa, B., Gamallo, P., Martín-Rodilla, P., & Martínez-Castaño, R. (2021). Hybrid intelligence strategies for identifying, classifying and analyzing political bots. Social Sciences, 10(10).
  • Gilbert, A.S. (2018). Algorithmic culture and the colonization of life-worlds. Thesis Eleven, 146, 87-96.
  • Graefe, A., Haim, M., Haarmann, B., & Brosius, H.B. (2018). Readers’ perception of computer-generated news: Credibility, expertise, and readability. Journalism, 19(5), 595-610.
  • Grant, M.J., & Booth, A. (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26, 91-108.
  • Graves, L., & Anderson, C.W. (2020). Discipline and promote: Building infrastructure and managing algorithms in a “structured journalism” project by professional fact-checking groups. New Media and Society, 22(2), 342-360.
  • Häring, M., Loosen, W., & Maalej, W. (2018). Who is addressed in this comment? Automatically classifying meta-comments in news comments. In K. Karahalios, A. Monroy-Hernández, A. Lampinen, & G. Fitzpatrick (Eds.), Proceedings of the ACM on Human-Computer Interaction (pp. 1-20).
  • Harper, T. (2017). The big data public and its problems: Big data and the structural transformation of the public sphere. New Media and Society, 19(9), 1424-1439.
  • Helberger, N. (2019). On the democratic role of news recommenders. Digital Journalism, 7(8), 993-1012.
  • Hepp, A. (2020). Artificial companions, social bots and work bots: communicative robots as research objects of media and communication studies. Media, Culture and Society, 42(7-8), 1410-1426.
  • Hermida, A., & Young, M.L. (2017). Finding the data unicorn: A hierarchy of hybridity in data and computational journalism. Digital Journalism, 5(2), 159-176.
  • Jamil, S. (2021). Automated journalism and the freedom of media: Understanding legal and ethical implications in competitive authoritarian regime. Journalism Practice.
  • Jones, R., & Jones, B. (2019). Atomising the news: The (in)flexibility of structured journalism. Digital Journalism, 7(8), 1157-1179.
  • Kaluža, J. (2021). Habitual generation of filter bubbles: Why is algorithmic personalisation problematic for the democratic public sphere? Javnost.
  • Kotenidis, E., & Veglis, A. (2021). Algorithmic journalism-Current Applications and Future Perspectives. Journalism and Media, 2(2), 244-257.
  • Kunert, J., & Thurman, N. (2019). The form of content personalisation at mainstream, transatlantic news outlets. Journalism Practice, 13(7), 759-780.
  • Leong, B. (2019). Facial recognition and the future of privacy: I always feel like… somebody’s watching me. Bulletin of the Atomic Scientists, 75(3), 109-115.
  • Lewis, S.C., Guzman, A.L., & Schmidt, T.R. (2019). Automation, journalism, and human-machine communication: Rethinking roles and relationships of humans and machines in news. Digital Journalism, 7(4), 409-427.
  • López-García, X., & Vizoso, A. (2021). Periodismo de alta tecnología: Signo de los tiempos digitales del tercer milenio. Profesional de la Información, (pp. 30-30).
  • Makhortykh, M., & Wijermars, M. (2021). Can filter bubbles protect information freedom? Discussions of algorithmic news recommenders in Eastern Europe. Digital Journalism.
  • Martin, F.R. (2021). Visibility, connectivity, agency: Journalism’s prospects in an age of automated social news sharing. Digigal Journalism, 9(8), 1190-1198.
  • Milosavljevi, M., & Vobi, I. (2019). Human still in the loop: Editors reconsider the ideals of professional journalism through automation. Digital Journalism, 7(8), 1098-1116.
  • Møller-Hartley, J., Bengtsson, M., Hansen, A.S., & Sivertsen, M.F. (2021). Researching publics in datafied societies: Insights from four approaches to the concept of ‘publics’ and a (hybrid) research agenda. New Media and Society.
  • Montal, T., & Reich, Z. (2017). I, robot. You, journalist. Who is the author? Authorship, bylines and full disclosure in automated journalism. Digital Journalism, 5(7), 829-849.
  • Ohme, J. (2021). Algorithmic social media use and its relationship to attitude reinforcement and issue-specific political participation-The case of the 2015 European immigration movements. Journal of Information Technology and Politics, 18(1), 36-54.
  • Papakyriakopoulos, O., Hegelich, S., Shahrezaye, M., & Serrano, J.C.M. (2018). Social media and microtargeting: Political data processing and the consequences for Germany. Big Data and Society, 5(2), 1-15.
  • Parratt-Fernández, S., Mayoral-Sánchez, J., & Mera-Fernández, M. (2021). The application of artificial intelligence to journalism: An analysis of academic production. Profesional de la Información, (pp. 30-30).
  • Piñeiro-Naval, V., & Morais, R. (2019). Study of the academic production on communication in Spain and Latin America. [Estudio de la producción académica sobre comunicación en España e Hispanoamérica]. Comunicar, 61, 113-123.
  • Powers, E. (2017). My news feed is filtered? Awareness of news personalization among college students. Digital Journalism, 5(10), 1315-1335.
  • Puschmann, C. (2019). Beyond the bubble: Assessing the diversity of political search results. Digital Journalism, 7(6), 824-843.
  • Santini, R.M., Agostini, L., Barros, C.E., Carvalho, D., De-Rezende, R.C., Salles, D.G., Seto, K., Terra, C., & Tucci, G. (2018). Software power as soft power: A literature review on computational propaganda effects in public opinion and political process. 11, 332-360.
  • Schapals, A.K., & Porlezza, C. (2020). Assistance or resistance? Evaluating the intersection of automated journalism and journalistic role conceptions. Media and Communication, 8(3), 16-26.
  • Schjøtt-Hansen, A., & Hartley, J.M. (2021). Designing what’s news: An ethnography of a personalization algorithm and the data-driven (re)assembling of the news. Digital Journalism.
  • Seaver, N. (2018). Captivating algorithms: Recommender systems as traps. Journal of Material Culture, 24(4), 421-436.
  • Sehl, A., Cornia, A., & Nielsen, R.K. (2021). How do funding models and organizational legacy shape news organizations’ social media strategies? A comparison of public service and private sector news media in six countries. Digital Journalism.
  • Shahnazi, A.F., & Afifi, T.F. (2017). Strategies for literature reviews. In M. Allen (Ed.), The SAGE Encyclopedia of Communication Research Methods. SAGE.
  • Shmargad, Y., & Klar, S. (2020). Sorting the news: how ranking by popularity polarizes our politics. Political Communication, 37(3), 423-446.
  • Slaek-Brlek, S., Smrke, J., & Vobi, I. (2017). Engineering technologies for journalism in the digital age: A case study. Digital Journalism, 5(8), 1025-1043.
  • Tandoc, E.C., Yao, L.J., & Wu, S. (2020). Man vs. machine? The impact of algorithm authorship on news credibility. Digital Journalism, 8(4), 548-562.
  • Thorson, K., Cotter, K., Medeiros, M., & Pak, C. (2021). Algorithmic inference, political interest, and exposure to news and politics on Facebook. Information Communication and Society, 24(2), 183-200.
  • Thurman, N. (2018). Social media, surveillance, and news work: On the apps promising journalists a ‘crystal ball. Digital Journalism, 6(1), 76-97.
  • Thurman, N., Dörr, K., & Kunert, J. (2017). When reporters get hands-on with robo-writing: Professionals consider automated journalism’s capabilities and consequences. Digital Journalism, 5(10), 1240-1259.
  • Thurman, N., Lewis, S.C., & Kunert, J. (2019). Algorithms, automation, and news. Digital Journalism, 7(8), 980-992.
  • Tong, J., & Zuo, L. (2021). The inapplicability of objectivity: Understanding the work of data journalism. Journalism Practice, 15(2), 153-169.
  • Turner-Lee, N. (2018). Detecting racial bias in algorithms and machine learning. Journal of Information, Communication and Ethics in Society, 16(3), 252-260.
  • Vállez, M., & Codina, L. (2018). Periodismo computacional: evolución, casos y herramientas. Profesional de la Información, 27(4), 759-768.
  • Van-Dijck, J. (2020). Governing digital societies: Private platforms, public values. Computer Law and Security Review, 36, 105377-105377.
  • Van-Dijck, J., Poell, T., & De-Waal, M. (2018). The platform society: Public values in a connective world. Oxford University Press.
  • Waddell, T.F. (2018). A robot wrote this? How perceived machine authorship affects news credibility. Digital Journalism, 6(2), 236-255.
  • Weber, M.S., & Kosterich, A. (2018). Coding the news: The role of computer code in filtering and distributing news. Digital Journalism, 6(3), 310-329.
  • Wölker, A., & Powell, T.E. (2021). Algorithms in the newsroom? News readers’ perceived credibility and selection of automated journalism. Journalism, 22(1), 86-103.
  • Wu, S., Tandoc, E.C., & Salmon, C.T. (2019). Journalism reconfigured: Assessing human-machine relations and the autonomous power of automation in news production. Journalism Studies, 20(10), 1440-1457.
  • Yarchi, M., Baden, C., & Kligler-Vilenchik, N. (2020). Political polarization on the digital sphere: A cross-platform, over-time analysis of interactional, positional, and affective polarization on social media. Political Communication, 38, 98-139.
  • Zerback, T., Töpfl, F., & Knöpfle, M. (2021). The disconcerting potential of online disinformation: Persuasive effects of astroturfing comments and three strategies for inoculation against them. New Media and Society, 23(5), 1080-1098.
  • Ziewitz, M. (2017). A not quite random walk: Experimenting with the ethnomethods of the algorithm. Big Data and Society, 4(2).