Yapay zekâ araçlarında trol davranış algısı ölçeğinin geliştirilmesi

Abstract

Bu çalışmada, yapay zeka araçlarıyla ilişkili olarak trol davranışına ilişkin algıları ölçmek için geçerli ve güvenilir bir ölçek geliştirilmiştir. Dijital teknolojiler ve yapay zeka tabanlı uygulamalar, eğitim de dahil olmak üzere çeşitli alanlarda giderek yaygınlaştıkça, çevrimiçi trolllemenin potansiyel sosyal ve psikolojik etkilerini inceleme ihtiyacı artmıştır. Eğitim ortamlarında, güvenli, etik ve sağlıklı bir dijital etkileşim ortamı sağlamak, bu tür davranışların ölçülebilir olmasını gerektirir. Veriler, farklı yaş gruplarını temsil eden 300 katılımcıdan çevrimiçi bir anket yoluyla toplanmıştır; katılımcıların %33,7'si erkek ve %66,3'ü kadındır. Katılımcıların çoğu 18-24 ve 25-31 yaşları arasındadır. Veri toplama aracı, 22 maddelik, beş faktörlü, 5 puanlık Likert ölçeğidir. Faktörler arasında saldırgan ve düşmanca davranışlar, veri manipülasyonu, sosyal provokasyon, anonimlik ve çoklu kimlikler ile duygusal manipülasyon yer almaktadır. Keşifsel Faktör Analizi (EFA), bu boyutlarla uyumlu beş faktörlü bir yapı ortaya koyarak toplam varyansın %74,135'ini açıklamış ve ölçeğin yapı geçerliliğini desteklemiştir. Doğrulayıcı Faktör Analizi (CFA), alt boyutlar ve ölçek maddeleri arasında istatistiksel olarak anlamlı ilişkiler göstererek ölçüm modelini daha da doğrulamıştır. Genel olarak, bulgular ölçeğin, özellikle eğitim bağlamlarında, yapay zeka ile ilgili araçların trol davranışı algıları üzerindeki etkisini değerlendirmek için geçerli ve güvenilir bir araç olduğunu göstermektedir.

Keywords

• yapay zeka davranışı
• ölçek geliştirme
• trol davranış

Development of a Troll Behavior Perception Scale in Artificial Intelligence Tools

Abstract

This study developed a valid and reliable scale to measure perceptions of troll behavior in artificial intelligence tools. As digital technologies and AI-based applications become increasingly widespread across various fields, including education, the need to examine the potential social and psychological effects of online trolling has grown. In educational settings, ensuring a safe, ethical, and healthy digital interaction environment requires that such behaviors be measurable. The study used convenient sampling methods to reach participants from 300 different age groups and 33.7% of this group were male and 66.3% were female. Most participants were between the ages of 18 and 31. The data collection instrument was a 22-item, five-factor, 5-point Likert scale. The factors included aggressive and hostile behaviors, data manipulation, social provocation, anonymity and multiple identities, and emotional manipulation. Exploratory Factor Analysis (EFA) revealed a five-factor structure aligned with these dimensions, explaining 74.135% of the total variance and supporting the construct validity of the scale. Confirmatory Factor Analysis (CFA) further validated the measurement model by demonstrating statistically significant relationships between subdimensions and scale items. Overall, the findings demonstrate that the scale is a valid and reliable tool for assessing the influence of AI-related tools on perceptions of troll behavior, particularly within educational contexts.

Keywords

• Artificial intelligence behavior
• scale development
• troll behavior

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