Trending Topics on Metaverse: A Microblog Text Analysis with BERT and DTM
He Chaocheng1,2,Huang Qian1,Li Xinru1,Wang Chunying3,Wu Jiang1()
1School of Information Management, Wuhan University, Wuhan 430072, China 2Shenzhen Research Institute of Wuhan University, Shenzhen 518052, China 3School of Information Management, Zhengzhou University, Zhengzhou 450018, China
[Objective] This paper comprehensively examines the evolution of public opinion triggered by the metaverse concepts, which provides insights for metaverse-related policies and industry planning. [Methods] We retrieved Weibo textual posts on metaverse-related from September 2021 to February 2023. Then, we utilized BERT and DTM models to extract semantic and topic features. Third, we employed the K-means algorithm for topic clustering and explored their evolutionary patterns. [Results] The public attention on the metaverse originated around NFTs and gaming. With capital speculation within the digital industry, the entertainment and physical industries joined the race. The emergence of ChatGPT further prompted the public’s exploration of the status quo of the metaverse, technology innovation, and prospective applications. [Limitations] We did not include foreign language data from Twitter to compare the focus and trends of the metaverse topics among domestic and international users. [Conclusions] This study examines the characteristics and evolution of social attention on topics related to the meta-universe from quantitative and macro perspectives. It helps us regulate online public opinion in the meta-universe.
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He Chaocheng, Huang Qian, Li Xinru, Wang Chunying, Wu Jiang. Trending Topics on Metaverse: A Microblog Text Analysis with BERT and DTM. Data Analysis and Knowledge Discovery, 2023, 7(9): 25-38.
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