@inproceedings{9742f3333a104701b2178e8169e1c155,
title = "Analyzing Bias of Comments on Political News Articles to Facilitate Transparent Online Communities",
abstract = "Comments on the news articles can affect people's perceptions and behaviors. However, little is known about how people determine the degree of bias (DoB) of comments on political news articles. To address such bias issues, current platforms of news articles offer criteria to sort multiple comments on the news articles. However, little is known about whether the DoB of comments is reduced when publishers offer various criteria for sorting comments. We conducted surveys to identify how people determine DoB of comments on the news article, and how bias varies depending on how comments are sorted. The findings of this study revealed that there was a significant difference among the DoB by comments. Future work remains to develop an algorithm generating unbiased comments by using existing comments on political news articles and their DoB.",
keywords = "Bias, Comments, Degree of bias, Online communities, Online news, Political news, Sorting criteria, Top comments",
author = "Joonho Gwon and Minji Kwon and Hyunggu Jung",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 2020 Symposium on Emerging Research from Asia and on Asian Contexts and Cultures, AsianCHI 2020 - Part of CHI 2020 ; Conference date: 25-04-2020",
year = "2020",
month = apr,
day = "25",
doi = "10.1145/3391203.3391216",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "49--52",
booktitle = "AsianCHI 2020 - Proceedings of the 2020 Symposium on Emerging Research from Asia and on Asian Contexts and Cultures, Part of CHI 2020",
}