Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
38th (2024)
Session ID : 4C1-GS-11-05
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Exploring Data Analysis Methods on X (Formerly Twitter) Using BERTopic:
A Case Study on “Self-Responsibility” Posts during the COVID-19 Pandemic
*Shinnosuke KURASAWAKeisuke HINODEShinichiro WADA
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

The COVID-19 pandemic caused chaos across various facets of life, from politics and economy to social activities. Faced with the extreme difficulty of completely preventing infection, we were compelled to make public health choices, including self-restraint and vaccination. However, because these choices were not enforceable, discrepancies in individual norms led to problems. Against this backdrop, a discourse questioning 'self-responsibility' emerged on Twitter. In Japanese society, 'self-responsibility' is a peculiar concept, increasingly used in discussions of social issues related to poverty, such as welfare dependency and the working poor. This concept has been extensively researched in the social sciences, including sociology. In this study, using BERTopic, the latest topic modeling tool that employs c-TF-IDF, we reveal the nature of "self-responsibility" under the unique circumstances of the COVID-19 crisis. By utilizing c-TF-IDF akin to a table of contents, we could elucidate perspectives on self-responsibility during the pandemic from both pregnant individuals and medical professionals.

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© 2024 The Japanese Society for Artificial Intelligence
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