Kamuoyunun Dijital Tanıklığı: Uluslararası Haberlerde Gazze Üzerine Kullanıcı Söylemlerinin Duygu ve Konu Temelli Analizi

Abstract

Bu çalışma, Gazze çatışmasına ilişkin uluslararası haber kanallarının YouTube’da yayımlanan videoları altındaki kullanıcı yorumlarını inceleyerek haber çerçevelemesi ile izleyici alımlaması arasındaki etkileşimi hesaplamalı sosyal bilimler yaklaşımıyla analiz etmektedir. Veri seti, “Gazze” anahtar kelimesini içeren ve yüksek izlenme oranına sahip 11 uluslararası haber kuruluşuna ait videolardan elde edilen kullanıcı yorumlarından oluşmaktadır. Yorumlar üzerinde BERT tabanlı duygu analizi, BERTopic konu modellemesi, kelime frekansı analizi, bigram analizi ve kelime birliktelik ağı gibi doğal dil işleme (NLP) yöntemleri uygulanmış; böylece dijital söylemin duygusal, insani ve politik bileşenleri çok katmanlı biçimde ortaya konmuştur. Bulgular, kullanıcı tepkilerinin büyük ölçüde negatif duygular, insani kayıplara odaklanmış değerlendirmeler, rehineler ve siviller etrafında şekillenen kriz temelli söylemler ile politik aktörlere ilişkin tartışmalarda yoğunlaştığını göstermektedir. Farklı haber kanallarının çatışmayı sunuş biçimleri, kullanıcı yorumlarında anlamlı söylemsel ayrışmalar üretmiş; görsel şiddet, yıkım düzeyi, trajedik hikâyeler ve politik çerçeveler yorumların duygusal tonunu belirgin biçimde etkilemiştir. Araştırma, hesaplamalı yöntemler kullanarak uluslararası haber içeriklerinin dijital ortamda duygusal kamuların oluşumunu nasıl yönlendirdiğini ortaya koymakta ve çatışma haberciliğinde çerçeveleme–alımlama ilişkisine veri temelli, özgün bir katkı sunmaktadır.

Keywords

• Gazze
• Haber Çerçeveleme
• Dijital Kamuoyu
• Hesaplamalı Sosyal Bilimler
• Duygu Analizi
• Konu Modelleme

Public Opinion's Digital Testimony: Sentiment and Topic-Based Analysis of User Discourse on Gaza in International News

Abstract

This study analyzes the interaction between news framing and audience reception using a computational social science approach by examining user comments under videos published on YouTube by international news channels related to the Gaza conflict. The dataset consists of user comments obtained from videos belonging to 11 international news organizations that contain the keyword “Gaza” and have high viewership rates. Natural language processing (NLP) methods such as BERT-based sentiment analysis, BERTopic topic modeling, word frequency analysis, bigram analysis, and word co-occurrence networks were applied to the comments, thus revealing the emotional, human, and political components of digital discourse in a multi-layered manner. The findings show that user reactions largely centered on negative emotions, assessments focused on human losses, crisis-based discourse shaped around hostages and civilians, and discussions about political actors. The ways in which different news channels presented the conflict produced meaningful discursive differences in user comments; visual violence, the level of destruction, tragic stories, and political frameworks significantly influenced the emotional tone of the comments. Using computational methods, the research reveals how international news content shapes the formation of emotional publics in the digital environment and offers a data-driven, original contribution to the framing–reception relationship in conflict journalism.

Keywords

• Gaza
• News Framing
• Digital Public Opinion
• Computational Social Sciences
• Sentiment Analysis
• Topic Modeling

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