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YAPAY ZEKÂ VE ALGORİTMİK KÜLTÜR BAĞLAMINDA SOSYAL MEDYA DENEYİMİNİN GELECEĞİ ÜZERİNE BİR DEĞERLENDİRME

Year 2023, Volume: 7 Issue: 3, 216 - 237, 07.09.2023

Abstract

Web 3.0 teknolojilerinin internet ortamları üzerinde artan etkisiyle birlikte yapay zekânın ve kişiselleştirme özelliğinin kullanıcıların dijital ortamlardaki deneyimlerini şekillendirmeye başladığı görülmektedir. Bu bağlamda, sosyal medya şirketlerinin yapay zekâ yatırımlarını artırması ve öneri algoritmalarını geliştirmesi ile kullanıcıların sosyal medya deneyiminde kişiselleştirilmiş içerikler giderek daha fazla önem kazanmıştır. Bu bağlamda, algoritmalarla şekillenmiş dijital platformların gündelik hayatın içerisindeki etkisinin artması ile birlikte bilişimsel sistemlerin kültürel unsurlar üzerindeki yansımalarının netleşmesine vurgu yapan algoritmik kültür kavramı (Galloway, 2006; Striphas, 2015) öne çıkmaya başlamıştır.


Bu araştırmanın amacı gelişen yapay zekâ teknolojileri ve algoritmik kültür bağlamında sosyal medya deneyiminin geleceğinin değerlendirilmesidir. Yapay zekâ teknolojilerinin sosyal medya platformlarında giderek artan rolünü yorumlamak amacıyla gerçekleştirilen araştırmada derinlemesine görüşme yöntemi kullanılarak dijital pazarlama, sosyal medya, yapay zekâ, veri ve kullanıcı deneyimi alanlarından 8 uzmanın görüşü değerlendirilmiştir. Araştırma katılımcılarının çoğunun algoritmik kültürü değerlendirirken ayrımcılık, eşitlik, ön yargı konularında vurgu yaptıkları görülmektedir. Araştırma bulguları kapsamında sosyal medya şirketlerinin aktivitelerine ilişkin “sorumlu yapay zekâ” üzerine çalışmalar yapılmasının önemi ve gerekliliği vurgulanmaktadır.

References

  • Alvarado, O.,Waern, A., (2018). Towards Algorithmic Experience: Initial Efforts for Social Media Contexts. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). Association for Computing Machinery, New York, NY, USA, Paper 286, 1–12.
  • Brown, B., Chui, M., & Manyika, J. (2011). Are You Ready For The Era Of ‘Big Data’. Mckinsey Quarterly, 4(1), 24-35.
  • Bozdağ, E. (2013). Bias in algorithmic filtering and personalization. Ethics Inf Technol 15, 209–227.
  • Chandra, S., Verma, S., Lım, W. M., Kumar, S., & Donthu, N. (2022). Personaliza-tion in personalized marketing: Trends and ways forward. Psychology & Marketing, 1529-1562.
  • Cheney-Lıppold, J. (2011) A New Algorithmic Identity: Soft Biopolitics and the Modulation of Control. Theory, Culture & Society, 28(6), 164–181.
  • Claes, A., Wıard, V., Mercenıer, H., Phılıppette, T., Dufrasne, M., Browet, A., Jungers, R., Algorithmes de Recommandation et Culture Technique: Penser le Dialogue Entre Education et Design, Tic&Société, 15(1):127-157.
  • Cotter, K., & Reisdorf, B. C. (2020). Algorithmic Knowledge Gaps: A New Dimension of (Digital) Inequality. International Journal of Communication (Ijoc), 2020(14), 745–765.
  • Devito, M. A. (2021). Adaptive Folk Theorization as a Path to Algorithmic Literacy on Changing Platforms. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 1–38.
  • Dıonısıo, J. D., Burns Iıı, W. G., Ve Gılbert, R. (2013). 3D Virtual Worlds and the Metaverse: Current Status and Future Possibilities. ACM Computing Surveys, 45(3), 1-38.
  • Dogruel, L. (2021). What is Algorithm Literacy? A Conceptualization and Challenges of It’s Empirical Measurement. In C. Schumann & M. Taddicken (Eds.), Algorithms and Communication. Special Issue of Digital Communication Research.
  • Dogruel, L., Masur, P., Joeckel, S. (2022) Development and Validation of an Algorithm Literacy Scale for Internet Users, Communication Methods and Measures, 16:2, 115-133.
  • Fuchs C. (2014). Sosyal Medya Eleştirel Bir Giriş. Ankara: Notabene Yayınları.
  • Galloway, C. & Swıatek, L., (2018). Public Relations and Artificial Intelligence: It’s Not (Just) About Robots. Public Relations Review, 44(5).
  • Galloway Ar (2006). Gaming: Essays on Algorithmic Culture. Minneapolis, MN: University of Minnesota Press.
  • Gillespie, T. (2014). Relevance of Algorithms. In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Inside Technology. Media Technologies: Essays on Communication, Materiality, and Society (pp. 167–194). The MIT Press.
  • Gran, A. -. B., Booth, P., & Bucher, T. (2021). To be or Not to be Algorithm Aware: A Question of a New Digital Divide? Information, Communication & Society, 24(12), 1779–1796.
  • Güçdemir, Y., (2015). Sanal Ortamda İletişim Bir Halkla İlişkiler Perspektifi. İstanbul: Derin Yayınları Doneda, D., Almeida, V. A. F. (2016) "What Is Algorithm Governance?," in IEEE Internet Computing, vol. 20, no. 4, pp. 60-63, July-Aug. 2016, doi: 10.1109/MIC.2016.79.
  • Head, A. J., Fister, B., & Macmillan, M. (2020, January 15). Information Literacy in the Age of Algorithms: Student Experiences With News and Information, and The Need for Change. Project Information Literacy. https://files.eric.ed.gov/fulltext/ ED605109.pdf
  • Johanssen, J., (2019). Series: Routledge Studies in New Media and Cyberculture. London: Routledge.
  • Kara, T., (2017). Gençler Neden Snapchat Kullaniyor Kullanımlar Ve Doyumlar Yaklaşımı Üzerinden Bir Araştırma. Intermedia International E-Journal, 3 (5), 262-277.
  • Keshab, N., (2022): Evolution of The Internet from Web 1.0 to Metaverse: The Good, The Bad and The Ugly. TechRxiv. Koenig, A., (2020). The Algorithms Know Me and I Know Them: Using Student Journals to Uncover Algorithmic Literacy Awareness, Computers and Composition, 58, 102611,ISSN 8755-4615.
  • Kotler, P., Kartajaya, H., Setıawan, I., (2022). Pazarlama 5.0, İstanbul: Nişantaşı Üniversitesi Yayınları.
  • Kuş, O., (2021). Algoritmaları Dehümanizasyon Çerçevesinde Tartışmak (Der. Oğuz Kuş). Algoritmaların Gölgesinde Toplum Ve İletişim. Ankara: Alternatif Bilişim Derneği.
  • Lafrance, S., (2017), Qui A Peur Du Big Data?, Gestion 1 (Vol. 42), s. 6-6.
  • Leavy, S. (2018, May). Gender Bias in Artificial Intelligence: The Need for Diversity and Gender Theory in Machine Learning. In Proceedings of the 1st international workshop on gender equality in software engineering (pp. 14-16).
  • Lutz, C. (2019). Digital Inequalities in the Age of Artificial Intelligence and Big Data. Human Behavior and Emerging Technologies, 1(2), 141–148.
  • Narin, B. (2018). Kişiselleştirilmiş Çevrimiçi Haber Akışının Yankı Odası Etkisi, Filtre Balonu ve Siberbalkanizasyon Kavramları Çerçevesinde Incelenmesi. Selçuk İletişim, 11(2), 232-251.
  • Özkök Şişman, Ö. (2023). Metaverse ve Dijital Reklamcılıkekseninde Hiper Kişiselleştirilmiş Reklamların Yükselişi. İçinde S. K. Yıldız (Ed.). Metaverse: Yeni Gerçeklik Paradigmaları (s. 147-160). Ankara: Nobel Yayınları.
  • Palmer, D. E. (2005). Pop-ups, cookies, and spam: toward a deeper analysis of the ethical significance of internet marketing practices. Journal of business ethics, 58, 271-280.
  • Pariser, E. (2011). The Filter Bubble: What the Internet is Hiding From You. Londres, Royaume-Uni : Penguin Books.
  • Pavlik, J., (2008). Mapping the Consequences of Technology on Public Relations.
  • Reviglio, U. Ve Agosti, C. (2020). Thinking Outside the Black-Box: The Case for “Algorithmic Sovereignty” in Social Media. Social Media + Society, 1- 12.
  • Roberge, J., Seyfert, S., (2016). What are Algorithmic Cultures? in Algoritmic Cultures Essays on Meaning, Performance and New Technologies, Ed. Seyfert R., Roberge J. London and New York: Routledge.
  • Sin, S. C. J., & Kim, K. S. (2013). International students' everyday life information seeking: The informational value of social networking sites. Library & Information Science Research, 35(2), 107-116.
  • Smith, J., Mccarthy, J. D., Mcphail, C., & Augustyn, B. (2001). From Protest to Agenda Building: Description Bias in Media Coverage of Protest Events in Washington, D.C. Social Forces, 79(4), 1397–1423.
  • Striphas, T. (2015). Algorithmic Culture. European Journal of Cultural Studies, 18(4- 5): 395-412.
  • Sunikka, A., & Bragge, J. (2012). Applying Text-Mining to Personalization and Customization Research Literature–Who, What and Where? Expert Systems with Applications, 39(11), 10049– 10058. Sunstein, C. R. (2001). Republic.Com 2.0. Princeton, NJ: Princeton University Press.
  • Sunstein, C. R. (2004). Democracy and Filtering, December 2014, Vol. 47, No.12, 57-59.
  • Swart J., (2021) Experiencing Algorithms: How Young People Understand, Feel About, and Engage With Algorithmic News Selection on Social Media, Social Media + Socety, 7 (2).
  • Şener, G., (2021). Algoritmalara Karşı Aktivist Taktikler, Der. Oğuz Kuş. Algoritmaların Gölgesinde Toplum ve İletişim. Ankara: Alternatif Bilişim Derneği
  • Till, C. (2014). Exercise as Labour: Quantified Self and the Transformation of Exercise into Labour, Societies, 4(3), ss. 1-17.
  • Willson, M., (2016). Algorithms (and the) Everyday, Information, Communication & Society.
  • Yildirim, A., & Şimşek, H. (2016). Sosyal Bilimlerde Nitel Araştırma Yöntemleri. Ankara: Seçkin Yayınları.

An Assessment on the Future of Social Media Experience in the Context of Artificial Intelligence and Algorithmic Culture

Year 2023, Volume: 7 Issue: 3, 216 - 237, 07.09.2023

Abstract

With the increasing influence of Web 3.0 technologies on online environments, it is observed that artificial intelligence and personalization features are beginning to shape users' experiences in digital contexts. In this context, the concept of algorithmic culture (Galloway, 2006; Striphas, 2015),which emphasizes the clarification of the reflections of computational systems on cultural elements as the impact of alghorithmically shaped digital platforms increases in everyday life, has emerged.

The purpose of this study is to evaluate the future of the social media experience within the context of evolving artificial intelligence technologies and algorithmic culture. To interpret the growing role of artificial intelligence technologies on social media platforms, in-depth interview method was employed, and the perspectives of 8 experts from the fields of digital marketing, social media, artificial intelligence, data, and user experience were evaluated. The majority of the research participants are observed to emphasize issues of discrimination, equality, and bias when evaluating the topic of algorithmic culture. Within the scope of the research findings, the importance and necessity of conducting studies on "responsible AI" regarding the activities of social media companies are emphasized.

References

  • Alvarado, O.,Waern, A., (2018). Towards Algorithmic Experience: Initial Efforts for Social Media Contexts. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). Association for Computing Machinery, New York, NY, USA, Paper 286, 1–12.
  • Brown, B., Chui, M., & Manyika, J. (2011). Are You Ready For The Era Of ‘Big Data’. Mckinsey Quarterly, 4(1), 24-35.
  • Bozdağ, E. (2013). Bias in algorithmic filtering and personalization. Ethics Inf Technol 15, 209–227.
  • Chandra, S., Verma, S., Lım, W. M., Kumar, S., & Donthu, N. (2022). Personaliza-tion in personalized marketing: Trends and ways forward. Psychology & Marketing, 1529-1562.
  • Cheney-Lıppold, J. (2011) A New Algorithmic Identity: Soft Biopolitics and the Modulation of Control. Theory, Culture & Society, 28(6), 164–181.
  • Claes, A., Wıard, V., Mercenıer, H., Phılıppette, T., Dufrasne, M., Browet, A., Jungers, R., Algorithmes de Recommandation et Culture Technique: Penser le Dialogue Entre Education et Design, Tic&Société, 15(1):127-157.
  • Cotter, K., & Reisdorf, B. C. (2020). Algorithmic Knowledge Gaps: A New Dimension of (Digital) Inequality. International Journal of Communication (Ijoc), 2020(14), 745–765.
  • Devito, M. A. (2021). Adaptive Folk Theorization as a Path to Algorithmic Literacy on Changing Platforms. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 1–38.
  • Dıonısıo, J. D., Burns Iıı, W. G., Ve Gılbert, R. (2013). 3D Virtual Worlds and the Metaverse: Current Status and Future Possibilities. ACM Computing Surveys, 45(3), 1-38.
  • Dogruel, L. (2021). What is Algorithm Literacy? A Conceptualization and Challenges of It’s Empirical Measurement. In C. Schumann & M. Taddicken (Eds.), Algorithms and Communication. Special Issue of Digital Communication Research.
  • Dogruel, L., Masur, P., Joeckel, S. (2022) Development and Validation of an Algorithm Literacy Scale for Internet Users, Communication Methods and Measures, 16:2, 115-133.
  • Fuchs C. (2014). Sosyal Medya Eleştirel Bir Giriş. Ankara: Notabene Yayınları.
  • Galloway, C. & Swıatek, L., (2018). Public Relations and Artificial Intelligence: It’s Not (Just) About Robots. Public Relations Review, 44(5).
  • Galloway Ar (2006). Gaming: Essays on Algorithmic Culture. Minneapolis, MN: University of Minnesota Press.
  • Gillespie, T. (2014). Relevance of Algorithms. In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Inside Technology. Media Technologies: Essays on Communication, Materiality, and Society (pp. 167–194). The MIT Press.
  • Gran, A. -. B., Booth, P., & Bucher, T. (2021). To be or Not to be Algorithm Aware: A Question of a New Digital Divide? Information, Communication & Society, 24(12), 1779–1796.
  • Güçdemir, Y., (2015). Sanal Ortamda İletişim Bir Halkla İlişkiler Perspektifi. İstanbul: Derin Yayınları Doneda, D., Almeida, V. A. F. (2016) "What Is Algorithm Governance?," in IEEE Internet Computing, vol. 20, no. 4, pp. 60-63, July-Aug. 2016, doi: 10.1109/MIC.2016.79.
  • Head, A. J., Fister, B., & Macmillan, M. (2020, January 15). Information Literacy in the Age of Algorithms: Student Experiences With News and Information, and The Need for Change. Project Information Literacy. https://files.eric.ed.gov/fulltext/ ED605109.pdf
  • Johanssen, J., (2019). Series: Routledge Studies in New Media and Cyberculture. London: Routledge.
  • Kara, T., (2017). Gençler Neden Snapchat Kullaniyor Kullanımlar Ve Doyumlar Yaklaşımı Üzerinden Bir Araştırma. Intermedia International E-Journal, 3 (5), 262-277.
  • Keshab, N., (2022): Evolution of The Internet from Web 1.0 to Metaverse: The Good, The Bad and The Ugly. TechRxiv. Koenig, A., (2020). The Algorithms Know Me and I Know Them: Using Student Journals to Uncover Algorithmic Literacy Awareness, Computers and Composition, 58, 102611,ISSN 8755-4615.
  • Kotler, P., Kartajaya, H., Setıawan, I., (2022). Pazarlama 5.0, İstanbul: Nişantaşı Üniversitesi Yayınları.
  • Kuş, O., (2021). Algoritmaları Dehümanizasyon Çerçevesinde Tartışmak (Der. Oğuz Kuş). Algoritmaların Gölgesinde Toplum Ve İletişim. Ankara: Alternatif Bilişim Derneği.
  • Lafrance, S., (2017), Qui A Peur Du Big Data?, Gestion 1 (Vol. 42), s. 6-6.
  • Leavy, S. (2018, May). Gender Bias in Artificial Intelligence: The Need for Diversity and Gender Theory in Machine Learning. In Proceedings of the 1st international workshop on gender equality in software engineering (pp. 14-16).
  • Lutz, C. (2019). Digital Inequalities in the Age of Artificial Intelligence and Big Data. Human Behavior and Emerging Technologies, 1(2), 141–148.
  • Narin, B. (2018). Kişiselleştirilmiş Çevrimiçi Haber Akışının Yankı Odası Etkisi, Filtre Balonu ve Siberbalkanizasyon Kavramları Çerçevesinde Incelenmesi. Selçuk İletişim, 11(2), 232-251.
  • Özkök Şişman, Ö. (2023). Metaverse ve Dijital Reklamcılıkekseninde Hiper Kişiselleştirilmiş Reklamların Yükselişi. İçinde S. K. Yıldız (Ed.). Metaverse: Yeni Gerçeklik Paradigmaları (s. 147-160). Ankara: Nobel Yayınları.
  • Palmer, D. E. (2005). Pop-ups, cookies, and spam: toward a deeper analysis of the ethical significance of internet marketing practices. Journal of business ethics, 58, 271-280.
  • Pariser, E. (2011). The Filter Bubble: What the Internet is Hiding From You. Londres, Royaume-Uni : Penguin Books.
  • Pavlik, J., (2008). Mapping the Consequences of Technology on Public Relations.
  • Reviglio, U. Ve Agosti, C. (2020). Thinking Outside the Black-Box: The Case for “Algorithmic Sovereignty” in Social Media. Social Media + Society, 1- 12.
  • Roberge, J., Seyfert, S., (2016). What are Algorithmic Cultures? in Algoritmic Cultures Essays on Meaning, Performance and New Technologies, Ed. Seyfert R., Roberge J. London and New York: Routledge.
  • Sin, S. C. J., & Kim, K. S. (2013). International students' everyday life information seeking: The informational value of social networking sites. Library & Information Science Research, 35(2), 107-116.
  • Smith, J., Mccarthy, J. D., Mcphail, C., & Augustyn, B. (2001). From Protest to Agenda Building: Description Bias in Media Coverage of Protest Events in Washington, D.C. Social Forces, 79(4), 1397–1423.
  • Striphas, T. (2015). Algorithmic Culture. European Journal of Cultural Studies, 18(4- 5): 395-412.
  • Sunikka, A., & Bragge, J. (2012). Applying Text-Mining to Personalization and Customization Research Literature–Who, What and Where? Expert Systems with Applications, 39(11), 10049– 10058. Sunstein, C. R. (2001). Republic.Com 2.0. Princeton, NJ: Princeton University Press.
  • Sunstein, C. R. (2004). Democracy and Filtering, December 2014, Vol. 47, No.12, 57-59.
  • Swart J., (2021) Experiencing Algorithms: How Young People Understand, Feel About, and Engage With Algorithmic News Selection on Social Media, Social Media + Socety, 7 (2).
  • Şener, G., (2021). Algoritmalara Karşı Aktivist Taktikler, Der. Oğuz Kuş. Algoritmaların Gölgesinde Toplum ve İletişim. Ankara: Alternatif Bilişim Derneği
  • Till, C. (2014). Exercise as Labour: Quantified Self and the Transformation of Exercise into Labour, Societies, 4(3), ss. 1-17.
  • Willson, M., (2016). Algorithms (and the) Everyday, Information, Communication & Society.
  • Yildirim, A., & Şimşek, H. (2016). Sosyal Bilimlerde Nitel Araştırma Yöntemleri. Ankara: Seçkin Yayınları.
There are 43 citations in total.

Details

Primary Language Turkish
Subjects Communication Technology and Digital Media Studies
Journal Section Research Article
Authors

Ceren Bilgici 0000-0002-7510-8185

Publication Date September 7, 2023
Submission Date August 11, 2023
Acceptance Date September 5, 2023
Published in Issue Year 2023 Volume: 7 Issue: 3

Cite

APA Bilgici, C. (2023). YAPAY ZEKÂ VE ALGORİTMİK KÜLTÜR BAĞLAMINDA SOSYAL MEDYA DENEYİMİNİN GELECEĞİ ÜZERİNE BİR DEĞERLENDİRME. Yeni Medya Elektronik Dergisi, 7(3), 216-237.


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