Federe Sosyal Ağlarda Yapay Zekâya Yönelik Duygular ve Algılar: Hesaplamalı Bir Analiz

Abstract

Bu çalışma, federe sosyal ağlarda, özellikle Bluesky ve Mastodon’da yapay zekâya yönelik toplumsal algıyı incelemeyi amaçlamaktadır. Mevcut araştırmalar merkezi platformlara odaklanmasına rağmen, merkeziyetsiz ağlarda yapay zekâ algısı konusunda önemli bir araştırma boşluğu bulunmaktadır. Bu çalışma, Bluesky ve Mastodon’daki yapay zekâyla ilişkili gönderilerin hesaplamalı analiziyle bu boşluğu doldurmayı hedeflemektedir. 1 Ocak 2023 - 1 Ocak 2025 tarihleri arasında Bluesky ve Mastodon’dan toplanan 61.285 gönderiye veri olarak metin (text-as-data) yaklaşımı uygulanmıştır. Yapay zekâ söylemindeki baskın temaları, duygu durumunu ve tartışma örüntülerini belirlemek için konu modellemesi, duygu analizi ve metin analizi yöntemleri birlikte kullanılmıştır. Her iki platformda da yapay zekâya karşı genel olarak olumlu bir tutum gözlemlenmiştir; güven, beklenti ve sevinç temel duygusal tepkileri oluştururken, bu duyguların altında korku ve endişe de yer almaktadır. Platform bazında belirgin farklılıklar ortaya çıkmıştır: Mastodon’daki tartışmalar yaratıcılık, dijital sanat ile yapay zekânın toplumsal ve etik sonuçları üzerine yoğunlaşırken; Bluesky’daki gönderiler girişimler, finansman, borsa ve uluslararası politika gibi ekonomik ve jeopolitik boyutlara odaklanmaktadır. Araştırma, kamusal söylemde yapay zekâ algısına dair önemli bir parçalanmanın varlığını ortaya koymaktadır; tartışmalar platformlarda ekonomik ve etik alanlar şeklinde ayrışmaktadır. Bu durum farklı toplumsal grupların görüşlerine alan yaratsa da, yapay zekâ yönetişimi konusunda geniş toplumsal uzlaşı sağlamakta zorluklara yol açmaktadır. Geliştirilen analitik çerçeve, merkeziyetsiz sosyal ağ dinamiklerini anlamaya katkı sunmakta ve bu alandaki politika geliştiricilere önemli bulgular sağlamaktadır.

Keywords

• Yapay zekâ
• Kamu algısı
• Federe sosyal ağlar
• Metin analizi
• Duygu analizi

Ethical Statement

Bu çalışmada halka açık sosyal medya verileri kullanılmış olup, kişisel veya gizli bilgi içermediğinden etik kurul onayı gerektirmemektedir

Artificial Intelligence Related Sentiments and Perceptions on Federated Social Networks: A Computational Text Analysis

Abstract

This study aims to examine public perceptions of artificial intelligence (AI) on federated social networks, specifically Bluesky and Mastodon. While existing research focuses on centralized platforms, a significant gap exists regarding AI perception within decentralized networks. This study addresses this gap through computational analysis of AI related posts in Bluesky and Mastodon. A text-as-data approach was employed to analyze 61,285 posts collected from Bluesky and Mastodon between January 1, 2023, and January 1, 2025. The methodology integrated topic modeling, sentiment analysis, and text analysis to identify prevalent themes, sentiment polarity, and discussion patterns within AI-related discourse. Findings demonstrate predominantly positive sentiment towards AI across both platforms, with trust, anticipation, and joy as primary emotional responses, accompanied by underlying fear and anxiety. Platform-specific variations emerged: Mastodon discourse centers on creativity, digital art, and societal-ethical implications including regulation, bias, and disinformation concerns. Conversely, Bluesky posts emphasize economic and geopolitical dimensions, featuring startups, funding, stock markets, and international policy. The analysis reveals significant fragmentation in public AI perception, characterized by discourse division into distinct economic and ethical spheres across platforms. While this fragmentation accommodates diverse social group perspectives, it presents challenges for establishing comprehensive societal consensus on AI governance. The analytical framework provides insights for understanding decentralized social network dynamics and implications for policy makers examining AI perception in federated digital environments.

Keywords

• Artificial intelligence
• Public perception
• Federated social networks
• Text analysis
• Sentiment analysis

Ethical Statement

This study used publicly available social media data and did not require ethics committee approval as it did not involve personal or confidential information.

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