TY - JOUR T1 - ANALYSING USER SATISFACTION OF DIGITAL CONTENT PLATFORMS IN TURKEY WITH ARTIFICIAL INTELLIGENCE TT - TÜRKİYE'DE DİJİTAL İÇERİK PLATFORMLARI KULLANICI MEMNUNİYETİNİN YAPAY ZEKÂ İLE ANALİZİ AU - Kayakuş, Mehmet AU - Sine, Sıla Nur PY - 2025 DA - November Y2 - 2025 DO - 10.20875/makusobed.1740855 JF - Mehmet Akif Ersoy University Journal of Social Sciences Institute JO - MAKU SOBED PB - Burdur Mehmet Akif Ersoy University WT - DergiPark SN - 1309-1387 SP - 105 EP - 121 IS - 42 LA - en AB - This study analyses user satisfaction with digital content platforms in Turkey through user comments using artificial intelligence and text mining techniques. The 1,400 comments collected over a seven-month period were classified as positive, negative, and neutral using the TextBlob library, and emotional trends were visualised with word frequencies and word clouds. The findings show that user satisfaction fluctuates over time; positive comments increase in February and March, while neutral attitudes come to the fore in June and July. In particular, the frequent use of content-orientated expressions such as ‘scenario’, ‘series’ and ‘character’ reveals that audience feedback is shaped by thematic elements. The study provides strategic recommendations for content development and user experience management on digital platforms. KW - User Satisfaction KW - Digital Content Platforms KW - Artificial Intelligence KW - Sentiment Analysis KW - Text Mining N2 - Bu çalışma, Türkiye’deki dijital içerik platformlarına yönelik kullanıcı memnuniyetini, kullanıcı yorumları üzerinden yapay zekâ ve metin madenciliği teknikleriyle analiz etmektedir. Yedi aylık süreçte toplanan 1.400 yorum; TextBlob kütüphanesi ile olumlu, olumsuz ve nötr olarak sınıflandırılmış; kelime frekansları ve kelime bulutlarıyla duygusal eğilimler görselleştirilmiştir. Bulgular, kullanıcı memnuniyetinin zaman içinde dalgalandığını; Şubat ve Mart aylarında olumlu yorumların arttığını, Haziran ve Temmuz’da ise nötr tutumların öne çıktığını göstermektedir. Özellikle “senaryo”, “dizi”, “karakter” gibi içerik odaklı ifadelerin sık kullanılması, izleyici geri bildirimlerinin tematik unsurlar üzerinden şekillendiğini ortaya koymaktadır. Çalışma, dijital platformlar için içerik geliştirme ve kullanıcı deneyimi yönetimi açısından stratejik öneriler sunmaktadır. CR - Alrizq, M., & Alghamdi, A. (2024). Customer satisfaction analysis with Saudi Arabia mobile banking apps: a hybrid approach using text mining and predictive learning techniques. Neural Computing and Applications, 36(11), 6005-6023. https://doi.org/10.1007/s00521-023-09400-4 CR - Abdullah, D. (2025). Proposal: Evaluating user satisfaction in mobile medical applications using text mining and sentiment analysis. Journal of Computational Medicine and Informatics, 52-61. 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İktisadi İdari ve Siyasal Araştırmalar Dergisi, 7(17), 47-67. https://doi.org/10.25204/iktisad.970186 UR - https://doi.org/10.20875/makusobed.1740855 L1 - https://dergipark.org.tr/en/download/article-file/5048664 ER -