Mapping Literature and Research Trends on AI Applications in Journalism: A Bibliometric Review
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Abstract
An emerging field of interdisciplinary research that needs more focus is the application of AI in journalism. The bibliometric analysis of the most recent research on implementation in digital journalism is presented in this paper. From Scopus, publications from 2014 to 2023 were examined to determine subjects, performance, impact, and collaborations. The findings indicate a rise in yearly production, with over 88 publications released in 2023 attesting to heightened research activity. Additionally, more recent publications had a more significant citation effect, demonstrating their relevance today. The majority of the prolific writers are from America, China, and Spain. International collaborations are centered around the West, between the United States and China, and the United States and Korea. This offers a standard that will guide future research in this enormously promising field. For AI to be implemented in digital journalism in a responsible manner, under-represented groups must be more involved.
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References
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[2] T. Sakirin and S. Kusuma, “A Survey of Generative Artificial Intelligence Techniques,” Babylonian Journal of Artificial Intelligence, vol. 2023, pp. 10–14, Mar. 2023, doi: 10.58496/BJAI/2023/003.
[3] R. Doshi and K. K. Hiran, “Decision Making and IoT: Bibliometric Analysis for Scopus Database,” Babylonian Journal of Internet of Things, vol. 2023, pp. 13–22, Mar. 2023, doi: 10.58496/BJIoT/2023/003.
[4] I. A. Bykov and M. V. Medvedeva, “Media Literacy and AI-technologies in Digital Communication: opportunities and Risks,” in 2024 Communication Strategies in Digital Society Seminar (ComSDS), IEEE, Apr. 2024, pp. 21–24. doi: 10.1109/ComSDS61892.2024.10502053.
[5] W. (Eric) Jang, J. W. Chun, S. Kim, and Y. W. Kang, “The Effects of Anthropomorphism on How People Evaluate Algorithm-Written News,” Digital Journalism, vol. 11, no. 1, pp. 103–124, Jan. 2023, doi: 10.1080/21670811.2021.1976064.
[6] J. V. Pavlik, Disruption and Digital Journalism. London: Routledge, 2021. doi: 10.4324/9781003111788.
[7] R. Jones and B. Jones, “Atomising the News: The (In)Flexibility of Structured Journalism,” Digital Journalism, vol. 7, no. 8, pp. 1157–1179, Sep. 2019, doi: 10.1080/21670811.2019.1609372.
[8] J. Mayoral Sánchez, S. Parratt Fernández, and M. Mera Fernández, “Uso periodístico de la IA en medios de comunicación españoles: mapa actual y perspectivas para un futuro inmediato,” Estudios sobre el Mensaje Periodístico, vol. 29, no. 4, pp. 821–832, Dec. 2023, doi: 10.5209/esmp.89193.
[9] V. Moravec, N. Hynek, M. Skare, B. Gavurova, and M. Kubak, “Human or machine? The perception of artificial intelligence in journalism, its socio-economic conditions, and technological developments toward the digital future,” Technol Forecast Soc Change, vol. 200, p. 123162, Mar. 2024, doi: 10.1016/j.techfore.2023.123162.
[10] T. Forja-Pena, B. García-Orosa, and X. López-García, “The Ethical Revolution: Challenges and Reflections in the Face of the Integration of Artificial Intelligence in Digital Journalism,” Communication & Society, pp. 237–254, Jun. 2024, doi: 10.15581/003.37.3.237-254.
[11] T. Forja-Pena, B. García-Orosa, and X. López-García, “A Shift Amid the Transition: Towards Smarter, More Resilient Digital Journalism in the Age of AI and Disinformation,” Soc Sci, vol. 13, no. 8, p. 403, Jul. 2024, doi: 10.3390/socsci13080403.
[12] T. T. N. Trang, P. Chien Thang, L. D. Hai, V. T. Phuong, and T. Q. Quy, “Understanding the Adoption of Artificial Intelligence in Journalism: An Empirical Study in Vietnam,” Sage Open, vol. 14, no. 2, Apr. 2024, doi: 10.1177/21582440241255241.
[13] N. Donthu, S. Kumar, D. Mukherjee, N. Pandey, and W. M. Lim, “How to conduct a bibliometric analysis: An overview and guidelines,” J Bus Res, vol. 133, pp. 285–296, 2021, doi: https://doi.org/10.1016/j.jbusres.2021.04.070.
[14] I. Zupic and T. Čater, “Bibliometric Methods in Management and Organization,” Organ Res Methods, vol. 18, no. 3, pp. 429–472, Dec. 2014, doi: 10.1177/1094428114562629.
[15] M. Fauzi, M. Nguyễn, and A. Malik, “Knowledge sharing and theory of planned behavior: a bibliometric analysis,” Journal of Knowledge Management, vol. 28, May 2023, doi: 10.1108/JKM-11-2022-0933.
[16] J. Cloudy, J. Banks, and N. D. Bowman, “The Str(AI)ght Scoop: Artificial Intelligence Cues Reduce Perceptions of Hostile Media Bias,” Digital Journalism, vol. 11, no. 9, pp. 1577–1596, Oct. 2023, doi: 10.1080/21670811.2021.1969974.
[17] B. Jones, R. Jones, and E. Luger, “AI ‘Everywhere and Nowhere’: Addressing the AI Intelligibility Problem in Public Service Journalism,” Digital Journalism, vol. 10, no. 10, pp. 1731–1755, Nov. 2022, doi: 10.1080/21670811.2022.2145328.
[18] J. Kuai, R. Ferrer-Conill, and M. Karlsson, “AI ≥ Journalism: How the Chinese Copyright Law Protects Tech Giants’ AI Innovations and Disrupts the Journalistic Institution,” Digital Journalism, vol. 10, no. 10, pp. 1893–1912, Nov. 2022, doi: 10.1080/21670811.2022.2120032.
[19] A. Stenbom, M. Wiggberg, and T. Norlund, “Exploring Communicative AI: Reflections from a Swedish Newsroom,” Digital Journalism, vol. 11, no. 9, pp. 1622–1640, Oct. 2023, doi: 10.1080/21670811.2021.2007781.
[20] N. Köbis and L. D. Mossink, “Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry,” Comput Human Behav, vol. 114, p. 106553, Jan. 2021, doi: 10.1016/j.chb.2020.106553.
[21] A. Lermann Henestrosa, H. Greving, and J. Kimmerle, “Automated journalism: The effects of AI authorship and evaluative information on the perception of a science journalism article,” Comput Human Behav, vol. 138, p. 107445, Jan. 2023, doi: 10.1016/j.chb.2022.107445.
[22] Y. Zheng, B. Zhong, and F. Yang, “When algorithms meet journalism: The user perception to automated news in a cross-cultural context,” Comput Human Behav, vol. 86, pp. 266–275, Sep. 2018, doi: 10.1016/j.chb.2018.04.046.