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Public attitudes and sentiments toward ChatGPT in China: A text mining analysis based on social media

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  • Lian, Ying
  • Tang, Huiting
  • Xiang, Mengting
  • Dong, Xuefan

Abstract

ChatGPT, an innovative artificial intelligence language model, is attracted significant attention around the world, sparking both enthusiasm and controversy, but identifying its societal impact and addressing its potential concerns necessitate an understanding of the prevailing public's attitudes toward the tool. In this study, we leverage text mining techniques to analyze the sentiments and themes prevalent among Chinese social media discussions of ChatGPT. In total, 96,435 comment data and 55,186 repost data were used, and the results show that public discussions mainly focused on ChatGPT's technical support, AI-related effectiveness, impact on human work, and effects on education and technology. Concerns were related to disinformation risks, technological unemployment, and the human–computer relationship. In addition, we found that social media played a prominent role in information dissemination, while official media and government units demonstrated a limited influence. The insights obtained through this study can inform policymakers, industry stakeholders, and the public of the public's prevailing attitude toward AI technologies, and they can facilitate informed decision-making.

Suggested Citation

  • Lian, Ying & Tang, Huiting & Xiang, Mengting & Dong, Xuefan, 2024. "Public attitudes and sentiments toward ChatGPT in China: A text mining analysis based on social media," Technology in Society, Elsevier, vol. 76(C).
    • Handle: RePEc:eee:teinso:v:76:y:2024:i:c:s0160791x23002476
    DOI: 10.1016/j.techsoc.2023.102442
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    1. Hua Bai & Guang Yu, 2016. "A Weibo-based approach to disaster informatics: incidents monitor in post-disaster situation via Weibo text negative sentiment analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 1177-1196, September.
    2. Pang, Hua & Liu, Jun & Lu, Jiahui, 2022. "Tackling fake news in socially mediated public spheres: A comparison of Weibo and WeChat," Technology in Society, Elsevier, vol. 70(C).
    3. Agarwal, Puneet & Aziz, Ridwan Al & Zhuang, Jun, 2022. "Interplay of rumor propagation and clarification on social media during crisis events - A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 714-733.
    4. Mahdi Hajiabadi & Hamed Vahdat-Nejad & Hamideh Hajiabadi, 2023. "COVID-19 and tourism: extracting public attitudes," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(4), pages 547-553, February.
    5. Wahyono, Budi & Rapih, Subroto & Boungou, Whelsy, 2023. "Unleashing the wordsmith: Analysing the stock market reactions to the launch of ChatGPT in the US Education sector," Finance Research Letters, Elsevier, vol. 58(PC).
    6. Eugène Loos & Johanna Gröpler & Marie-Louise Sophie Goudeau, 2023. "Using ChatGPT in Education: Human Reflection on ChatGPT’s Self-Reflection," Societies, MDPI, vol. 13(8), pages 1-18, August.
    7. Dong, Xuefan & Lian, Ying, 2021. "A review of social media-based public opinion analyses: Challenges and recommendations," Technology in Society, Elsevier, vol. 67(C).
    8. Holly Else, 2023. "Abstracts written by ChatGPT fool scientists," Nature, Nature, vol. 613(7944), pages 423-423, January.
    9. Xing, Yunfei & Wang, Xiwei & Qiu, Chengcheng & Li, Yueqi & He, Wu, 2022. "Research on opinion polarization by big data analytics capabilities in online social networks," Technology in Society, Elsevier, vol. 68(C).
    10. Wu, Zezhou & He, Qiufeng & Li, Jiarun & Bi, Guoqiang & Antwi-Afari, Maxwell Fordjour, 2023. "Public attitudes and sentiments towards new energy vehicles in China: A text mining approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    11. Jason Hung & Jackson Chen, 2023. "The Benefits, Risks and Regulation of Using ChatGPT in Chinese Academia: A Content Analysis," Social Sciences, MDPI, vol. 12(7), pages 1-15, June.
    12. Chaturvedi, Rijul & Verma, Sanjeev & Das, Ronnie & Dwivedi, Yogesh K., 2023. "Social companionship with artificial intelligence: Recent trends and future avenues," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    13. Perez-Castro, A. & Martínez-Torres, M.R. & Toral, S.L., 2023. "Efficiency of automatic text generators for online review content generation," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    14. Qianqian, Li & Yijun, Liu, 2020. "The China-Pakistan economic corridor: The Pakistani media attitudes perspective," Technology in Society, Elsevier, vol. 62(C).
    15. Yang, Zaoli & Wu, Qingyang & Venkatachalam, K. & Li, Yuchen & Xu, Bing & Trojovský, Pavel, 2022. "Topic identification and sentiment trends in Weibo and WeChat content related to intellectual property in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    16. Lee, Hyejun & Lee, Dong Il & Kim, Taeho & Lee, Juhyun, 2013. "The moderating role of socio-semantic networks on online buzz diffusion," Journal of Business Research, Elsevier, vol. 66(9), pages 1367-1374.
    17. Jianping Zhu & Futian Weng & Muni Zhuang & Xin Lu & Xu Tan & Songjie Lin & Ruoyi Zhang, 2022. "Revealing Public Opinion towards the COVID-19 Vaccine with Weibo Data in China: BertFDA-Based Model," IJERPH, MDPI, vol. 19(20), pages 1-26, October.
    18. Yanlong Guo & Lan Zu & Denghang Chen & Han Zhang, 2023. "A Study of Public Attitudes toward Shanghai’s Image under the Influence of COVID-19: Evidence from Comments on Sina Weibo," IJERPH, MDPI, vol. 20(3), pages 1-27, January.
    19. Hou, Shengjie & Zhang, Xiang & Yi, Biyi & Tang, Yi, 2022. "Public attitudes on open source communities in China: A text mining analysis," Technology in Society, Elsevier, vol. 71(C).
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