The Fallacy of Echo Chambers: Analyzing the Political Slants of User-Generated News Comments in Korean Media

Jiyoung Han1, Youngin Lee1, Junbum Lee2, Meeyoung Cha3
1Korea Advanced Institute of Science and Technology (KAIST), 2Seoul National Univ. of Education, 3Institute for Basic Science (IBS)


This study analyzes the political slants of user comments on Korean partisan media. We built a BERT-based classifier to detect political leaning of short comments via the use of semi-unsupervised deep learning methods that produced an F1 score of 0.83. As a result of classifying 27.1K comments, we found the high presence of conservative bias on both conservative and liberal news outlets. Moreover, this study discloses a considerable overlap of commenters across the partisan spectrum such that the majority of liberals (88.8%) and conservatives (63.7%) comment not only on news stories resonating with their political perspectives but also on those challenging their viewpoints. These findings advance the current understanding of online echo chambers.