Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

4-2021

Abstract

An echo chamber effect refers to the phenomena that online users revealed selective exposure and ideological segregation on political issues. Prior studies indicate the connection between the spread of misinformation and online echo chambers. In this paper, to help users escape from an echo chamber, we propose a novel news-analysis platform that provides a panoramic view of stances towards a particular event from different news media sources. Moreover, to help users better recognize the stances of news sources which published these news articles, we adopt a news stance classification model to categorize their stances into “agree”, “disagree”, “discuss”, or “unrelated” to a relevant claim for specified events with political stances. Finally, we proposed two ways showing the echo chamber effects: 1) visualizing the event and the associated pieces of news; and 2) visualizing the stance distribution of news from news sources of different political ideology. By making the echo chamber effect explicit, we expect online users will become exposed to more diverse perspectives toward a specific event. The demo video of our platform is available on Youtube.

Keywords

Echo Chamber, News Stance, Social Media Bias, Web Application

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media

Research Areas

Data Science and Engineering

Publication

WWW '21: Companion Proceedings of the Web Conference: Ljubljana, Slovenia, April 19-23

First Page

713

Last Page

716

ISBN

9781450383134

Identifier

10.1145/3442442.3458613

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3442442.3458613

Share

COinS