Host: The Japanese Society for Artificial Intelligence
Name : The 35th Annual Conference of the Japanese Society for Artificial Intelligence
Number : 35
Location : [in Japanese]
Date : June 08, 2021 - June 11, 2021
The phenomenon of filter bubbles and echo chambers has become a social issue. Our goal is to quantitatively evaluate these behaviors from log data. So far, we have discussed users' behavioral changes based on the diversity of article categories or vectors obtained from linguistic information of the titles. However, we believe that it is important to understand the characteristics of the behavior of users with specific interests in order to essentially understand issues such as filter bubbles. In this paper, we assessed the magnitude and change in user interest in the covid-19 against long-term data and analyzed the impact on engagement. We also showed that using the title information, which changes with time, as well as click logs allows for more accurate analysis of the news articles.
