Perceptions of the Future of Artificial Intelligence on Social Media: A Topic Modeling and Sentiment Analysis Approach

被引:0
|
作者
Ocal, Ayse [1 ]
机构
[1] Yildiz Tech Univ, Dept Comp Engn, TR-34220 Istanbul, Turkiye
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Artificial intelligence; BERT; BERTopic; sentiment analysis; topic modeling; TWITTER DATA; NEWS;
D O I
10.1109/ACCESS.2024.3510526
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 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.
引用
收藏
页码:182386 / 182409
页数:24
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