Dijital Seçmen Davranışı: X Üzerinden Siyasal Parti Algılarının Metin Madenciliği Yaklaşımıyla İncelenmesi

Abstract

Sosyal medya, kamuoyu ve toplumsal eğilimlerin analizinde önemli bir veri kaynağıdır. Bu çalışmada, Türkiye’deki beş siyasi partiye yönelik duygu eğilimleri, Türkçe tweetler üzerinden duygu analizi yöntemiyle incelenmiştir. X API aracılığıyla 11, 12 ve 14 Mayıs 2023 tarihlerinde toplanan 60.000’den fazla tweet içerisinden her parti için 250 olmak üzere toplam 1.250 tweet seçilmiştir. Tweetler pozitif, nötr ve negatif olarak sınıflandırılmış; Naive Bayes ve Karar Ağacı algoritmalarıyla analiz edilmiştir. Bulgular, algoritmaların benzer sınıflandırma performansı gösterdiğini ve duygu dağılımlarının parti ve duygu kategorisine göre değiştiğini ortaya koymaktadır. Çalışma, sosyal medya ve siyaset ilişkisini inceleyen araştırmalara katkı sağlamaktadır.

Keywords

• Duygu Analizi
• Metin Madenciliği
• Veri Madenciliği
• Sosyal Medya Analizi

Digital Voter Behavior: A Text Mining Approach to Analyzing Political Party Perceptions on X

Abstract

Social media provides an important source for analyzing public opinion and societal trends. This study examines sentiment toward five political parties in Türkiye using sentiment analysis of Turkish tweets. More than 60,000 tweets collected via the X API on May 11, 12, and 14, 2023, were used to select a balanced dataset of 1,250 tweets, with 250 tweets per party. Tweets were classified as positive, neutral, or negative and analyzed using Naive Bayes and Decision Tree algorithms. The results indicate similar classification performance between the two algorithms, while sentiment distributions varied across political parties and sentiment categories. The study contributes to research on the relationship between social media and politics by demonstrating the potential of sentiment analysis for evaluating political discourse.

Keywords

• Sentiment Analysis
• Text Mining
• Data Mining
• Social Media Analysis

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