Algoritmik Nostalji: Makine Öğrenimin Geçmişle Duygusal Bağlantılarımızı Şekillendirme Yöntemleri

Yıl 2025, Cilt: 16 Sayı: 3, 187 - 206, 31.08.2025

Bahtiyar Ahu Alpaslan , Ecemnur Delibalta

https://doi.org/10.5824/ajite.2025.03.001.x

Öz

Algoritmik olarak şekillenen medya ortamlarının giderek etkisini artırdığı günümüzde, nostalji dijital platformlar içinde güçlü bir duygusal araç hâline gelmiştir. Bu çalışma, Instagram ve Twitter’daki algoritmik öneri sistemlerinin nostalji temalı içeriklerin oluşumunu nasıl kolaylaştırdığını ve kullanıcıların duygusal katılımını nasıl etkilediğini incelemektedir. Marka hesapları tarafından paylaşılan geçmişe dönük içeriklerin, kolektif belleği harekete geçirecek biçimde nasıl kurgulandığı ve algoritmalar aracılığıyla görünürlük kazandığı analiz edilmiştir.
Çalışma, nitel dijital etnografi yöntemiyle yürütülmüş; Instagram ve Twitter’da seçilen halka açık marka hesapları üzerinde müdahalesiz gözlem yapılmıştır. Özellikle #TBT ve #ThrowbackThursday etiketleriyle paylaşılan içerikler incelenerek dijital nostaljinin algoritmalar yoluyla nasıl yeniden üretildiği değerlendirilmiştir. Bulgular, algoritmaların nostalji temalı içerikleri öne çıkararak kullanıcıların duygusal bağlarını ve topluluk hissini güçlendirdiğini, ancak aynı zamanda veri görünürlüğü ve kullanıcı özerkliği konularında endişeleri de artırdığını ortaya koymaktadır. Bazı kullanıcıların içeriklerle kurdukları etkileşimleri sonradan kaldırdıkları gözlemlenmiş, bu durum dijital etkileşimlerinin yarattığı görünürlük ya da sonuçlara dair bir rahatsızlık hissine işaret etmektedir.
Sonuç olarak, dijital nostaljinin duygusal sürekliliği teşvik ettiği kadar, kişiselleştirme ve veri etiği meselelerini de pekiştirdiği görülmektedir. Bu çalışma, duygusal deneyimle algoritmik arabuluculuk arasındaki ilişkiyi ele alarak, dijital kültürde duygusal bağlılık ve veri mahremiyetine dair endişelerin birlikte nasıl şekillendiğine dair derinlemesine bir anlayış sunmayı amaçlamaktadır.

Anahtar Kelimeler

Algoritmik Öneriler , Dijital Nostalji , Makine Öğrenmesi , Medya , İletişim

Algorithmic Nostalgia: How Machine Learning Curates Our Emotional Connections to the Past

Öz

In an era increasingly shaped by algorithmically curated media environments, nostalgia has become a powerful emotional tool within digital platforms. This study investigates how algorithmic recommendation systems on Instagram and Twitter facilitate the emergence of nostalgia-themed content and influence users' emotional engagement. The analysis explores how brand-generated throwback posts, strategically crafted to evoke collective memory and sentiment, intersect with user interaction patterns and algorithmic visibility mechanisms.
Using a qualitative digital ethnography approach, this research is based on non-intrusive observation of selected public brand accounts on Instagram and Twitter. Content using hashtags such as #TBT and #ThrowbackThursday was examined to understand how digital nostalgia is amplified through algorithmic circulation. The findings reveal that algorithm-driven promotion of nostalgic content not only enhances users’ emotional connectivity and sense of community but also generates concerns about data visibility and user autonomy. Some users were observed to later remove their engagements, suggesting a potential discomfort with the visibility or implications of their digital interactions.
The study highlights that digital nostalgia—while fostering emotional continuity—can also reinforce the complexities of personalization and data ethics in platform economies. By focusing on the interplay between emotional experience and algorithmic mediation, the study contributes to a deeper understanding of how affective engagement and concerns over data privacy co-evolve in contemporary digital culture.

Anahtar Kelimeler

Algorithmic Recommendations , Digital Nostalgia , Machine Learning , Media , Communicaiton

Kaynakça

• Acquisti, A. (2004). Privacy in electronic commerce and the economics of immediate gratification. Proceedings of the 5th ACM Conference on Electronic Commerce, 21–29. https://doi.org/10.1145/988772.988773
• Acquisti, A., Brandimarte, L., & Loewenstein, G. (2015). Privacy and human behavior in the age of information. Science, 347(6221), 509–514. https://doi.org/10.1126/science.aaa1465
• Akça, F. (2016). Siber güvenlikte insan faktörü ve sosyal mühendislik. Journal of Security Studies, 2(1), 58–65.
• Belk, R. W. (1990). The role of possessions in constructing and maintaining a sense of past. Advances in Consumer Research, 17, 669–676.
• Bolton, R. N., Parasuraman, A., Hoefnagels, A., Migchels, N., Kabadayi, S., Gruber, T., ... & Solnet, D. (2013). Understanding Generation Y and their use of social media: A review and research agenda. Journal of Service Management, 24(3), 245–267. https://doi.org/10.1108/09564231311326987
• Boym, S. (2001). The future of nostalgia. Basic Books.
• Bucher, T. (2018). If... then: Algorithmic power and politics. Oxford University Press.
• Chaney, A. J., Stewart, B. M., & Engelhardt, B. E. (2018). How algorithmic confounding in recommendation systems increases homogeneity and decreases utility. Proceedings of the 27th International Conference on World Wide Web, 239–248.
• Chen, X. (2020). Personalization and algorithmic curation in the digital age. Oxford University Press.
• Davidson, J., Liebald, B., Liu, J., Nandy, P., Van Vleet, T., Gargi, U., ... & Sampath, D. (2010). The YouTube video recommendation system. Proceedings of the Fourth ACM Conference on Recommender Systems, 293–296. https://doi.org/10.1145/1864708.1864770
• Davis, F. (1979). Yearning for yesterday: A sociology of nostalgia. Free Press.
• Fairclough, K. (2018). Classics in the streaming age: The formation and performance of cultural memory on Netflix. International Journal of Cultural Studies, 21(1), 25–41.
• Fisher, W. R. (1984). Narration as a human communication paradigm: The case of public moral argument. Communication Monographs, 51(1), 1–22.
• Gillespie, T. (2014). The politics of “platforms.” In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Media technologies: Essays on communication, materiality, and society (pp. 67–94). MIT Press.
• Gómez-Uribe, C. A., & Hunt, N. (2016). The Netflix recommender system: Algorithms, business value, and innovation. ACM Transactions on Management Information Systems, 6(4), Article 13. https://doi.org/10.1145/2843948
• Grainge, P. (2002). Monochrome memories: Nostalgia and style in retro America. Praeger.
• Guber, P. (2011). Tell to win: Connect, persuade, and triumph with the hidden power of story. Crown Business.
• Holbrook, M. B. (1993). Nostalgia and consumption preferences: Some emerging patterns of consumer tastes. Journal of Consumer Research, 20(2), 245–256.
• Kaplan, A. M., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
• Köksalan, H. (2022). Dijital ortamda kişisel verilerin korunması ve etik sorunlar. Academic Perspectives Journal, 4(3), 15–28.
• Leong, C. W., Beigman Klebanov, B., Hamill, C., Stemle, E., Ubale, R., & Chen, X. (2020). A report on the 2020 VUA and TOEFL metaphor detection shared task. Proceedings of the Second Workshop on Figurative Language Processing, 18–29. https://doi.org/10.18653/v1/2020.figlang-1.3
• Maersk [@maerskline]. (2015, July 9). We are posting this #tbt in honour of the iconic #MaerskMcKinneyMoller which celebrates two years of operational service this month! [Instagram post]. Instagram. https://www.instagram.com/p/5egnLkqexv/
• McKinsey & Company. (2024, November). What is psychological safety? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-psychological-safety
• Milligan, C. (2020). The affective mechanics of nostalgic media. New Media & Society, 22(3), 387–405.
• Niemeyer, K. (Ed.). (2014). Media and nostalgia: Yearning for the past, present and future. Palgrave Macmillan.
• Nissenbaum, H. (2010). Privacy in context: Technology, policy, and the integrity of social life. Stanford University Press.
• OECD. (1980). Guidelines on the protection of privacy and transborder flows of personal data. OECD Publishing.
• Official Gazette. (2016). Law No. 6698 on the Protection of Personal Data. Türkiye Cumhuriyeti Resmî Gazete.
• Pariser, E. (2011). The filter bubble: What the internet is hiding from you. Penguin Press.
• Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.
• Pepsi [@pepsi]. (2013, December 12). Showing some love on #ThrowbackThursday. <3 #TBT [Tweet]. X. Retrieved July 06, 2025, from https://x.com/pepsi/status/411217908476682240
• Ricci, F., Rokach, L., & Shapira, B. (Eds.). (2015). Recommender systems handbook (2nd ed.). Springer. https://doi.org/10.1007/978-1-4899-7637-6
• Rosenbaum, M. S., & Wong, I. A. (2015). If you remember, I’ll remember: Nostalgia, relationship maintenance, and Chinese consumers. Journal of Business Research, 68(11), 2346–2352.
• Scott, J. (2019). Cybersecurity and data protection: Trends and challenges. Cambridge Security Press.
• Sedikides, C., Wildschut, T., & Baden, D. (2004). Nostalgia: Past, present, and future. Current Directions in Psychological Science, 17(5), 304–307. https://doi.org/10.1111/j.1467-8721.2008.00595.x
• Smith, J. (2019). Understanding algorithmic personalization: A critical approach. Cambridge University Press.
• Solove, D. J. (2008). Understanding privacy. Harvard University Press.
• Tchakounté, F., Bellomo, D., & Gildas, L. (2020). Digital threat analysis in modern systems. Cybersecurity Advances, 7(3), 91–97.
• Tufekci, Z. (2014). Engineering the public: Big data, surveillance, and computational politics. First Monday, 19(7). https://doi.org/10.5210/fm.v19i7.4901
• Van Dijck, J. (2013). The culture of connectivity: A critical history of social media. Oxford University Press.
• Van Dijck, J. (2014). Datafication, dataism and dataveillance: Big data between scientific paradigm and ideology. Surveillance & Society, 12(2), 197–208. https://doi.org/10.24908/ss.v12i2.4776
• Zhang, C., Ko, M., & Carpenter, B. (2019). Exploring nostalgic engagement in social media: How memories and algorithms drive participation. International Journal of Social Media Studies, 6(2), 1–18.
• Zhang, S., & Chen, J. (2020). Explainable recommendation: A survey and new perspectives. Foundations and Trends® in Information Retrieval, 14(1), 1–101. https://doi.org/10.1561/1500000066
• Zuboff, S. (2015). Big other: Surveillance capitalism and the prospects of an information civilization. Journal of Information Technology, 30(1), 75–89. https://doi.org/10.1057/jit.2015.5
• Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.