Host: The Japanese Society for Artificial Intelligence
Name : The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, 2019
Number : 33
Location : [in Japanese]
Date : June 04, 2019 - June 07, 2019
In recent years, a lot of people pay attention to negative aspects of information publishing by individuals, such as fake news, flames and echo-chamber phenomena. However, information propagation on social media has become a large-scale and complicated phenomenon, and it is difficult for human beings to intuitively understand the whole picture. Therefore, we propose a method to visualize information propagation on social media in an intuitively understandable form in this paper. Specifically, in the proposed method a clustering method is applied recursively to a social network on Twitter and a hierarchical structure of user communities is constructed. We use the hierarchical structure to visualize information propagation. By using a hierarchical structure, we transform complex phenomena into simpler structures, thereby encouraging human intuitive understanding. We applied the proposed method to the actual case of large information propagation on Twitter and confirmed that reasonable visualization result can be obtained.