Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
36th (2022)
Session ID : 4H3-OS-2b-03
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Debunking Visualizer: A False-Mentioned Tweet Visualization System Considering User Information
*Makoto UEHARAShohei HISADAShoko WAKAMIYAEiji ARAMAKI
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

With the emergence of social media, anyone can send information and share it to many users easily. Accordingly, misinformation and disinformation, such as hoaxes and fake news, have spread more widely and rapidly than ever before. Echo chamber is an environment where one can only encounter information and opinions that reflect and reinforce one's own, which may foster the spread of fake news. Our goal in this study is to minimize the effects of echo chambers received by social media users. To help users step out of echo chambers, we developed a tweet visualization system. The system collects tweets containing "false rumor" or "fake news" words on Twitter and clusters them into several topics. We further visualize the buzzworthy changes of each topic by displaying clustered tweets in chronological order. Social media users can use the system to discover which topics they should pay attention to when they discuss.

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© 2022 The Japanese Society for Artificial Intelligence
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