JSAI2021
Jun 8 - Jun 30, 2021Online
JSAI2021
Jun 8 - Jun 30, 2021Online
[1D3-OS-3b-02]Controversial News Article Detection Method from Tweets
〇Yoshiki Fujikane1, Kazuhiro Kazama1, Mitsuo Yoshida2, Yoshinori Hijikata3(1. Wakayama University, 2. Toyohashi University of Technology, 3. Kwansei Gakuin University)
Keywords:
Twitter,news,controversy measure,polarization,network analysis
In this paper, we propose a method to automatically find controversial news articles in order to analyze the bias of opinion in mass media or social media.
First, we define the controversy measure of a news article using the number of users who mentioned it and the number of days that it were mentioned, assuming that news that causes controversy and debate in social media is mentioned by a limited but certain number of users for a relatively long period.
In addition, we analyze the polarization and cluster structure of media graphs and user graphs of specified news topics and the context, and verify whether we can find controversial news articles.
First, we define the controversy measure of a news article using the number of users who mentioned it and the number of days that it were mentioned, assuming that news that causes controversy and debate in social media is mentioned by a limited but certain number of users for a relatively long period.
In addition, we analyze the polarization and cluster structure of media graphs and user graphs of specified news topics and the context, and verify whether we can find controversial news articles.