The Fallacy of Echo Chambers: Analyzing the Political Slants of User-Generated News Comments in Korean Media
Jiyoung Han | Youngin Lee | Junbum Lee | Meeyoung Cha
Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019)
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 21.6K comments, we found the high presence of conservative bias on both conservative and liberal news outlets. Moreover, this study discloses an asymmetry across the partisan spectrum in that more liberals (48.0%) than conservatives (23.6%) 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.