Araştırma Makalesi
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Algoritmalar, Yapay Zeka ve Makine Öğrenimi Ekseninde Gazetecilik Etiği: Uluslararası Akademik Dergilere Yönelik Bir İnceleme

Yıl 2021, Cilt: 6 Sayı: 12, 296 - 327, 31.05.2021
https://doi.org/10.37679/trta.900086

Öz

Algoritmalar pek çok alanda olduğu gibi gazetecilikte de kullanılır hâle gelmiştir. Ancak bu durum, etik sorunları da beraberinde getirmiştir. Ayrıca algoritmalar geliştikçe etik sorunlar artmaya devam etmektedir. Bu nedenle bu çalışmada algoritma etiği üzerine odaklanılmıştır. Bu kapsamda gazetecilik alanıyla ilgili önde gelen üç dergi olan Digital Journalism, Journalism Studies ve Journalism & Mass Communication Quarterly’de 2019 ve 2020 yıllarında yayımlanmış algoritmalarla ilgili çalışmalar nitel içerik analizi yöntemi ile incelenmiştir. Alanda önde gelen bu dergilerde algoritma etiğine ne şekilde değinildiğini açığa çıkarmak hedeflenmiştir. Bu doğrultuda, makalelerin odaklarına, araştırmada kullanılan kuram/kavramlara, çalışmaların yöntemlerine, örneklemlerine, çalışmaların gerçekleştirildiği ülke ya da ülkelere ve algoritma etiğine yönelik bulgularına odaklanılmıştır. Sonuç olarak, gazetecilik alanında önde gelen bu dergilerde algoritmalara ilişkin çalışmalara fazla yer verilmediği, ayrıca çalışmaların çok azında etik sorunlara değinildiği açığa çıkmıştır. Algoritma etiğini araştıran sınırlı sayıda çalışmada ise algoritmalara dayalı etik ihlallerin, insanların tehlike altında hissetmeleri ya da suçsuz yere yargılanmaları gibi çeşitli sorunlara neden olabileceği ifade edilmiştir. Ayrıca bu çalışmaların etik sorunların çözümüne yönelik çeşitli yasal düzenlemeleri, makine öğrenimi teknolojisinin kullanımını, gerektiğinde insan kontrolünü ve algoritma seçimleri hakkında kullanıcıların bilgilendirilmesini önerdiği anlaşılmıştır.

Kaynakça

  • Ananny, M. (2016). Toward an ethics of algorithms: Convening, observation, probability, and timeliness. Science, Technology, & Human Values, 41(1), 93-117.
  • Ananny, M., & Crawford, K. (2018). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media & Society, 20(3), 973–989.
  • Anderson, C.W., Notas hacia un análisis del periodismo computacional (26 October, 2011). HIIG Discussion Paper Series No. 2012-1. Available at SSRN: https://ssrn.com/abstract=2009292 o http://dx.doi.org/10.2139/ssrn.2009292
  • Binark, M. (2017). Algoritmaların yarattığı yankı odalarında siyasal katılımın olanaksızlığı. Varlık, 1317, 19-23.
  • 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.
  • Bodó, B., Helberger, N., Eskens, S., & Möller, J. (2019). Interested in diversity: The role of user attitudes, algorithmic feedback loops, and policy in news personalization. Digital Journalism, 7(2), 206-229.
  • Bradshaw, P. (2014). “Data Journalism.” içinde Ethics for Digital Journalists: Emerging Best Practices, Lawrie Zion ve David Craig, Routledge, New York and London, 202-220.
  • Burrell, J. (2016). How the machine “thinks”: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 1–12.
  • Carlson, M. (2014). “The Robotic Reporter. Automated Journalism and the Redefinition of Labor, Compositional Forms, and Journalistic Authority.” Digital Journalism 3 (3): 416–431. doi: 10.1080/21670811.2014.976412.
  • Carlson, M. (2015). “The robotic reporter: automated journalism and the redefinition of labour, compositional forms, and journalistic authority”. Digital journalism 3(3), 416-431.
  • Carlson, M. (2018). “Automating judgment? Algorithmic judgment, news knowledge, and journalistic professionalism” New Media & Society, 20(5), 1755-1772.
  • Carlson, M. (2019). News algorithms, photojournalism and the assumption of mechanical objectivity in journalism. Digital Journalism, 7(8), 1117-1133.
  • Caswell, D. (2019). Structured journalism and the semantic units of news. Digital Journalism, 7(8), 1134-1156.
  • Cave, S., Nyrup, R., Vold, K., & Weller, A. (2018). Motivations and risks of machine ethics. Proceedings of the IEEE, 107(3), 562-574.
  • De Grove, F., Boghe, K., & De Marez, L. (2020). (What) Can Journalism Studies Learn from Supervised Machine Learning?. Journalism Studies, 21(7), 912-927.
  • Deuze, M. (2005). “What is Journalism?: Professional Identity and Ideology of Journalists Reconsidered.” Journalism 6 (4): 422–464.
  • Diakopoulos N. (2015). Algorithmic accountability: journalistic investigation of computational power structures. Digital Journalism 3(3): 398–415.
  • Diakopoulos, N. & Michael K. (2017). Algorithmic Transparency in the News Media, Digital Journalism, 5:7, 809-828, DOI: 10.1080/21670811.2016.1208053.
  • Diakopoulos, N. (2020). Computational News Discovery: Towards Design Considerations for Editorial Orientation Algorithms in Journalism. Digital Journalism, 8(7), 945-967.
  • Digital Journalism, Erişim adresi: https://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=rdij20, Erişim tarihi: 04.03.2021
  • Dörr, K. N., & Hollnbuchner, K. (2016). “Ethical Challenges of Algorithmic Journalism.” Digital Journalism. doi:10.1080/21670811.2016.1167612. edited by Lawrie Zion and David Craig, 202–219. New York: Routledge.
  • Ford, H., & Hutchinson, J. (2019). Newsbots that mediate journalist and audience relationships. Digital Journalism, 7(8), 1013-1031.
  • Gillespie, T. (2014). The relevance of algorithms. In Gillespie T., Boczkowski P., & Foot K., (Ed.) Media Technologies: Essays on Communication, Materiality, and Society (pp. 167- 194). Cambridge, MA: The MIT Press.
  • Grochowski J. R. & Ornstein, C. (2016). Matching Industry Payments to Medicare Prescribing Patterns: An Analysis. ProPublica Whitepaper. https://static.propublica.org/projects/d4d/20160317-matching-industry-payments.pdf?22.
  • Guzman, A. L. (2019). Prioritizing the Audience’s View of Automation in Journalism. Digital Journalism, 7(8), 1185-1190.
  • Haim, M. (2020). Agent-based Testing: An automated approach toward artificial reactions to human behavior. Journalism Studies, 21(7), 895-911.
  • Hansen, M., Roca-Sales, M., Keegan, J. & King, G. (2017). Artificial Intelligence: Practice and Implications for Journalism. Brown Institute for Media Innovation and the Tow Center for Digital Journalism.
  • Harambam J., Helberger N., van Hoboken J. (2018). Democratizing algorithmic news recommenders: how to materialize voice in a technologically saturated media ecosystem. Phil. Trans. R. Soc. A 376: 20180088.http://dx.doi.org/10.1098/rsta.2018.0088
  • Heald, D. (2006). Varieties of transparency. In C. Hood & D. Heald (Eds.), Transparency: The key to better governance? (pp. 25–46). Oxford, U.K.: Oxford University Press.
  • Helberger, N. (2019). On the democratic role of news recommenders. Digital Journalism, 7(8), 993-1012.
  • Jagadish, H.V. (2016). Data Science Ethics. Erişim: https://courses.edx.org/courses/course-v1:MichiganX+DS101x+3T2016/course/
  • Jameel, T., Ali, R., & Toheed, I. (2020, January). Ethics of Artificial Intelligence: Research Challenges and Potential Solutions. In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) (pp. 1-6). IEEE.
  • Jones, B., & Jones, R. (2019). Public service chatbots: Automating conversation with BBC News. Digital Journalism, 7(8), 1032-1053.
  • Jones, R., & Jones, B. (2019). Atomising the news: The (in) flexibility of structured journalism. Digital Journalism, 7(8), 1157-1179.
  • Journalism & Mass Communication Quarterly, Erişim adresi: https://journals.sagepub.com/aims-scope/JMQ, Erişim tarihi: 04.03.2021
  • Journalism Studies, Erişim adresi: https://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=rjos20, Erişim tarihi: 04.03.2021
  • Just, N., & Latzer, M. (2017). Governance by algorithms: Reality construction by algorithmic selection on the Internet. Media, Culture & Society, 39(2), 238-258. DOI: 10.1177/0163443716643157.
  • Kearns, M., & Roth, A. (2019). The ethical algorithm: The science of socially aware algorithm design. Oxford University Press.
  • Kraemer, F., Van Overveld, K., & Peterson, M. (2011). Is there an ethics of algorithms?. Ethics and information technology, 13(3), 251-260.
  • Leben, D. (2018). Ethics for robots: How to design a moral algorithm. Routledge.
  • 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.
  • Lewis, S. C., Sanders, A. K., & Carmody, C. (2019). Libel by Algorithm? Automated Journalism and the Threat of Legal Liability. Journalism & Mass Communication Quarterly, 96(1), 60–81. https://doi.org/10.1177/1077699018755983
  • Lewis, S. C., Sanders, A. K., & Carmody, C. (2019). Libel by algorithm? Automated journalism and the threat of legal liability. Journalism & Mass Communication Quarterly, 96(1), 60-81.
  • Lindén, C-G. (2017). “Algorithms for journalism: the future of news work”. The Journal of Media Innovations 4(1), 60-76. https://doi.org/10.5617/jmi.v4i1.2420
  • Liu, B., & Wei, L. (2019). Machine Authorship In Situ: Effect of news organization and news genre on news credibility. Digital Journalism, 7(5), 635-657.
  • Loecherbach, F., Moeller, J., Trilling, D., & van Atteveldt, W. (2020). The unified framework of media diversity: A systematic literature review. Digital Journalism, 8(5), 605-642.
  • Lu, S. (2020). Taming the News Feed on Facebook: Understanding Consumptive News Feed Curation through a Social Cognitive Perspective. Digital Journalism, 8(9), 1163-1180.
  • Martin, K. (2019). Ethical implications and accountability of algorithms. Journal of Business Ethics, 160(4), 835-850.
  • McBride, Kelly, ve Tom Rosenstiel (2014). “New Guiding Principles for a New Era of Journalism.” İçinde The New Ethics of Journalism, edited by Kelly McBride and Tom Rosenstiel, 1–6. Thousand Oaks, CA: CQ Press.
  • Milosavljević, M., & Vobič, I. (2019). Human still in the loop: Editors reconsider the ideals of professional journalism through automation. Digital journalism, 7(8), 1098-1116.
  • Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679.
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Journalism Ethics on the Axis of Algorithms, Artificial Intelligence and Machine Learning: A Review of International Academic Journals

Yıl 2021, Cilt: 6 Sayı: 12, 296 - 327, 31.05.2021
https://doi.org/10.37679/trta.900086

Öz

Algorithms have become used in journalism, as in many other fields. However, this situation has brought ethical problems with it. In addition, ethical problems continue to increase as algorithms evolve. Therefore, this study focused on algorithm ethics. In this context, studies on algorithms published in 2019 and 2020 in Digital Journalism, Journalism Studies and Journalism & Mass Communication Quarterly, which are three leading journals in the field of journalism, were examined. For this, content analysis method was used. It is aimed to reveal how algorithm ethics are mentioned in these leading journals in the field. In this direction, the focus of the articles, the theory/concepts used in the research, the methods of the studies, the samples, the country or countries where the studies were carried out, and the findings of algorithm ethics were focused. As a result, it has been revealed that these leading journals in the field of journalism do not have much coverage on algorithms, and that only a few of the studies address ethical issues. In a limited number of studies examining algorithm ethics, it has been stated that ethical violations based on algorithms can cause various problems such as people feeling in danger or being prosecuted innocently. Also it is revealed that, these studies suggests various legal regulations, the use of machine learning technology, human control when necessary, and informing of users about algorithm choices for the solution of ethical problems.

Kaynakça

  • Ananny, M. (2016). Toward an ethics of algorithms: Convening, observation, probability, and timeliness. Science, Technology, & Human Values, 41(1), 93-117.
  • Ananny, M., & Crawford, K. (2018). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media & Society, 20(3), 973–989.
  • Anderson, C.W., Notas hacia un análisis del periodismo computacional (26 October, 2011). HIIG Discussion Paper Series No. 2012-1. Available at SSRN: https://ssrn.com/abstract=2009292 o http://dx.doi.org/10.2139/ssrn.2009292
  • Binark, M. (2017). Algoritmaların yarattığı yankı odalarında siyasal katılımın olanaksızlığı. Varlık, 1317, 19-23.
  • 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.
  • Bodó, B., Helberger, N., Eskens, S., & Möller, J. (2019). Interested in diversity: The role of user attitudes, algorithmic feedback loops, and policy in news personalization. Digital Journalism, 7(2), 206-229.
  • Bradshaw, P. (2014). “Data Journalism.” içinde Ethics for Digital Journalists: Emerging Best Practices, Lawrie Zion ve David Craig, Routledge, New York and London, 202-220.
  • Burrell, J. (2016). How the machine “thinks”: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 1–12.
  • Carlson, M. (2014). “The Robotic Reporter. Automated Journalism and the Redefinition of Labor, Compositional Forms, and Journalistic Authority.” Digital Journalism 3 (3): 416–431. doi: 10.1080/21670811.2014.976412.
  • Carlson, M. (2015). “The robotic reporter: automated journalism and the redefinition of labour, compositional forms, and journalistic authority”. Digital journalism 3(3), 416-431.
  • Carlson, M. (2018). “Automating judgment? Algorithmic judgment, news knowledge, and journalistic professionalism” New Media & Society, 20(5), 1755-1772.
  • Carlson, M. (2019). News algorithms, photojournalism and the assumption of mechanical objectivity in journalism. Digital Journalism, 7(8), 1117-1133.
  • Caswell, D. (2019). Structured journalism and the semantic units of news. Digital Journalism, 7(8), 1134-1156.
  • Cave, S., Nyrup, R., Vold, K., & Weller, A. (2018). Motivations and risks of machine ethics. Proceedings of the IEEE, 107(3), 562-574.
  • De Grove, F., Boghe, K., & De Marez, L. (2020). (What) Can Journalism Studies Learn from Supervised Machine Learning?. Journalism Studies, 21(7), 912-927.
  • Deuze, M. (2005). “What is Journalism?: Professional Identity and Ideology of Journalists Reconsidered.” Journalism 6 (4): 422–464.
  • Diakopoulos N. (2015). Algorithmic accountability: journalistic investigation of computational power structures. Digital Journalism 3(3): 398–415.
  • Diakopoulos, N. & Michael K. (2017). Algorithmic Transparency in the News Media, Digital Journalism, 5:7, 809-828, DOI: 10.1080/21670811.2016.1208053.
  • Diakopoulos, N. (2020). Computational News Discovery: Towards Design Considerations for Editorial Orientation Algorithms in Journalism. Digital Journalism, 8(7), 945-967.
  • Digital Journalism, Erişim adresi: https://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=rdij20, Erişim tarihi: 04.03.2021
  • Dörr, K. N., & Hollnbuchner, K. (2016). “Ethical Challenges of Algorithmic Journalism.” Digital Journalism. doi:10.1080/21670811.2016.1167612. edited by Lawrie Zion and David Craig, 202–219. New York: Routledge.
  • Ford, H., & Hutchinson, J. (2019). Newsbots that mediate journalist and audience relationships. Digital Journalism, 7(8), 1013-1031.
  • Gillespie, T. (2014). The relevance of algorithms. In Gillespie T., Boczkowski P., & Foot K., (Ed.) Media Technologies: Essays on Communication, Materiality, and Society (pp. 167- 194). Cambridge, MA: The MIT Press.
  • Grochowski J. R. & Ornstein, C. (2016). Matching Industry Payments to Medicare Prescribing Patterns: An Analysis. ProPublica Whitepaper. https://static.propublica.org/projects/d4d/20160317-matching-industry-payments.pdf?22.
  • Guzman, A. L. (2019). Prioritizing the Audience’s View of Automation in Journalism. Digital Journalism, 7(8), 1185-1190.
  • Haim, M. (2020). Agent-based Testing: An automated approach toward artificial reactions to human behavior. Journalism Studies, 21(7), 895-911.
  • Hansen, M., Roca-Sales, M., Keegan, J. & King, G. (2017). Artificial Intelligence: Practice and Implications for Journalism. Brown Institute for Media Innovation and the Tow Center for Digital Journalism.
  • Harambam J., Helberger N., van Hoboken J. (2018). Democratizing algorithmic news recommenders: how to materialize voice in a technologically saturated media ecosystem. Phil. Trans. R. Soc. A 376: 20180088.http://dx.doi.org/10.1098/rsta.2018.0088
  • Heald, D. (2006). Varieties of transparency. In C. Hood & D. Heald (Eds.), Transparency: The key to better governance? (pp. 25–46). Oxford, U.K.: Oxford University Press.
  • Helberger, N. (2019). On the democratic role of news recommenders. Digital Journalism, 7(8), 993-1012.
  • Jagadish, H.V. (2016). Data Science Ethics. Erişim: https://courses.edx.org/courses/course-v1:MichiganX+DS101x+3T2016/course/
  • Jameel, T., Ali, R., & Toheed, I. (2020, January). Ethics of Artificial Intelligence: Research Challenges and Potential Solutions. In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) (pp. 1-6). IEEE.
  • Jones, B., & Jones, R. (2019). Public service chatbots: Automating conversation with BBC News. Digital Journalism, 7(8), 1032-1053.
  • Jones, R., & Jones, B. (2019). Atomising the news: The (in) flexibility of structured journalism. Digital Journalism, 7(8), 1157-1179.
  • Journalism & Mass Communication Quarterly, Erişim adresi: https://journals.sagepub.com/aims-scope/JMQ, Erişim tarihi: 04.03.2021
  • Journalism Studies, Erişim adresi: https://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=rjos20, Erişim tarihi: 04.03.2021
  • Just, N., & Latzer, M. (2017). Governance by algorithms: Reality construction by algorithmic selection on the Internet. Media, Culture & Society, 39(2), 238-258. DOI: 10.1177/0163443716643157.
  • Kearns, M., & Roth, A. (2019). The ethical algorithm: The science of socially aware algorithm design. Oxford University Press.
  • Kraemer, F., Van Overveld, K., & Peterson, M. (2011). Is there an ethics of algorithms?. Ethics and information technology, 13(3), 251-260.
  • Leben, D. (2018). Ethics for robots: How to design a moral algorithm. Routledge.
  • 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.
  • Lewis, S. C., Sanders, A. K., & Carmody, C. (2019). Libel by Algorithm? Automated Journalism and the Threat of Legal Liability. Journalism & Mass Communication Quarterly, 96(1), 60–81. https://doi.org/10.1177/1077699018755983
  • Lewis, S. C., Sanders, A. K., & Carmody, C. (2019). Libel by algorithm? Automated journalism and the threat of legal liability. Journalism & Mass Communication Quarterly, 96(1), 60-81.
  • Lindén, C-G. (2017). “Algorithms for journalism: the future of news work”. The Journal of Media Innovations 4(1), 60-76. https://doi.org/10.5617/jmi.v4i1.2420
  • Liu, B., & Wei, L. (2019). Machine Authorship In Situ: Effect of news organization and news genre on news credibility. Digital Journalism, 7(5), 635-657.
  • Loecherbach, F., Moeller, J., Trilling, D., & van Atteveldt, W. (2020). The unified framework of media diversity: A systematic literature review. Digital Journalism, 8(5), 605-642.
  • Lu, S. (2020). Taming the News Feed on Facebook: Understanding Consumptive News Feed Curation through a Social Cognitive Perspective. Digital Journalism, 8(9), 1163-1180.
  • Martin, K. (2019). Ethical implications and accountability of algorithms. Journal of Business Ethics, 160(4), 835-850.
  • McBride, Kelly, ve Tom Rosenstiel (2014). “New Guiding Principles for a New Era of Journalism.” İçinde The New Ethics of Journalism, edited by Kelly McBride and Tom Rosenstiel, 1–6. Thousand Oaks, CA: CQ Press.
  • Milosavljević, M., & Vobič, I. (2019). Human still in the loop: Editors reconsider the ideals of professional journalism through automation. Digital journalism, 7(8), 1098-1116.
  • Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679.
  • Monzer, C., Moeller, J., Helberger, N., & Eskens, S. (2020). User Perspectives on the News Personalisation Process: Agency, Trust and Utility as Building Blocks. Digital Journalism, 8(9), 1142-1162.
  • Myllylahti, M. (2020). Paying attention to attention: A conceptual framework for studying news reader revenue models related to platforms. Digital Journalism, 8(5), 567-575.
  • Narin, B. (2018). Kişiselleştirilmiş çevrim içi haber akışının yankı odası etkisi, filtre balonu ve siberbalkanizasyon kavramları çerçevesinde incelenmesi. Selçuk İletişim, 11(2), 232-251.
  • Newman, N. (2019). “Journalism, Media and Technology Trends and Predictions 2019”. Reuters Institute for the Study of Journalism.
  • Parmar, B., & Freeman, R. E. (2016). Ethics and the algorithm. MIT Sloan Management Review, 58(1), 16.
  • Pasquale F. (2015). The Black Box Society. Cambridge, MA: Harvard University Press.
  • Puschmann, C. (2019). Beyond the bubble: Assessing the diversity of political search results. Digital Journalism, 7(6), 824-843.
  • Raymond, A. H., & Shackelford, S. J. (2013). Technology, ethics, and access to justice: should an algorithm be deciding your case. Mich. J. Int'l L., 35, 485.
  • Richterich, A. (2018). The big data agenda: Data ethics and critical data studies (p. 154). University of Westminster Press.
  • Riffe, D., Lacy, S. ve Fico, F. (2005). Analyzing Media Messages: Using Quantitative Content Analysis In Research, New Jersey: Lawrence Erlbaum Associates, Inc.
  • Robinson, S., Lewis, S. C., & Carlson, M. (2019). Locating the “Digital” in Digital Journalism Studies: Transformations in Research. Digital Journalism, 7(3), 368-377.
  • Russell, F. M. (2019). The new gatekeepers: an Institutional-level view of Silicon Valley and the disruption of journalism. Journalism Studies, 20(5), 631-648.
  • Saurwein, F., & Spencer-Smith, C. (2020). Combating disinformation on social media: Multilevel governance and distributed accountability in Europe. Digital Journalism, 8(6), 820-841.
  • Schreier, M. (2012). Qualitative content analysis in practice. Thousands Oaks, CA: Sage.
  • Shearer, Matt, Basile Simon, and Clement Geiger (2014). “Datastringer: Easy Dataset Monitoring for Journalists.” Proceedings Symposium on Computation + Journalism.
  • SJR, Scimago Journal & Country Rank. Erişim adresi: https://www.scimagojr.com/aboutus.php, Erişim tarihi: 04.03.2021
  • Steiner, C. (2012) Automate This. New York: Portfolio/Penguin Press.
  • Stray, J. (2019). Making artificial intelligence work for investigative journalism. Digital Journalism, 7(8), 1076-1097.
  • Tandoc Jr, 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.
  • Thurman, N., Moeller, J., Helberger, N., & Trilling, D. (2019). My friends, editors, algorithms, and I: Examining audience attitudes to news selection. Digital Journalism, 7(4), 447-469.
  • Túñez-Lopez, M.; C. Toural-Bran, C. Valdiviezo-Abad (2019). “Automation, bots and algorithms in newsmaking. Impact and quality of artificial journalism”. Revista Latina de Comunicación Social, 74, 1411-1433 http://www.revistalatinacs.org/074paper/1391/74en.html DOI: 10.4185/RLCS-2019-1391en
  • Van Damme, K., Martens, M., Van Leuven, S., Vanden Abeele, M., & De Marez, L. (2020). Mapping the mobile DNA of news. Understanding incidental and serendipitous mobile news consumption. Digital Journalism, 8(1), 49-68.
  • Waddell, T. F. (2019). Can an Algorithm Reduce the Perceived Bias of News? Testing the Effect of Machine Attribution on News Readers’ Evaluations of Bias, Anthropomorphism, and Credibility. Journalism & Mass Communication Quarterly, 96(1), 82–100. https://doi.org/10.1177/1077699018815891
  • Wu, S., Tandoc Jr, E. C., & Salmon, C. T. (2019a). Journalism reconfigured: Assessing human–machine relations and the autonomous power of automation in news production. Journalism Studies, 20(10), 1440-1457.
  • Wu, S., Tandoc, E. C., & Salmon, C. T. (2019b). A Field Analysis of Journalism in the Automation Age: Understanding Journalistic Transformations and Struggles Through Structure and Agency. Digital Journalism, 7(4), 428-446.
  • Young, Mary L., and Alfred Hermida. 2014. “From Mr. and Mrs. Outlier to Central Tendencies.” Digital Journalism (online first), doi: 10.1080/21670811.2014.976409.
  • Zamith, R. (2019). Algorithms and Journalism, Oxford Research Encyclopedia of Communication, Subject: Journalism Studies Online Publication Date: Feb 2019, 1-21, DOI: 10.1093/acrefore/9780190228613.013.779
  • Zion, L. & Craig D. (2014). Ethics for Digital Journalists. Emerging Best Practices. New York: Routledge.
Toplam 79 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İletişim ve Medya Çalışmaları
Bölüm Makale
Yazarlar

Bahar Kayıhan 0000-0001-5196-4350

Bilge Narin 0000-0001-8717-6487

Demet Fırat 0000-0003-3369-2405

Feyyaz Fırat 0000-0002-9694-0747

Yayımlanma Tarihi 31 Mayıs 2021
Gönderilme Tarihi 20 Mart 2021
Kabul Tarihi 24 Mayıs 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 6 Sayı: 12

Kaynak Göster

APA Kayıhan, B., Narin, B., Fırat, D., Fırat, F. (2021). Algoritmalar, Yapay Zeka ve Makine Öğrenimi Ekseninde Gazetecilik Etiği: Uluslararası Akademik Dergilere Yönelik Bir İnceleme. TRT Akademi, 6(12), 296-327. https://doi.org/10.37679/trta.900086