Akademik Veri Yönetim Sistemi
IEEE ACCESS, cilt.1, ss.1-25, 2024 (SCI-Expanded)
Today’s AI technology has various applications in many fields, thus creating opportunities to improve different aspects of daily life and optimize business operations. However, there are also societal expectations and concerns regarding AI and its future impacts. Investigating such societal opinions and feelings is essential for social acceptance, further development and distribution of such technology, regulation, and adaptation to changes and policies. Despite this situation, such an exploration has not been sufficiently conducted in the existing literature and the most appropriate methods for such an exploration have not been sufficiently investigated. To contribute to addressing this limitation in the literature, this study applies topic modeling and sentiment analysis approaches to investigate societal opinions and feelings about the future of AI on social media, which includes conversations from various segments of society. A corpus consisting of 16,611 comments and 998 unique Reddit post titles was analyzed with a customized BERTopic model for topic modeling and a BERT sentiment classification model. This study highlights the significant advantages of using BERTopic and BERT models in analyzing a large sample of social media discussions. The results of this study can help realize the potential of text analytics methods through transformer-based language models to derive empirical findings from large-scale data samples.