Escape from An Echo Chamber

Kuan Chieh Lo, Shih Chieh Dai, Aiping Xiong, Jing Jiang, Lun Wei Ku

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


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 youtube1.

Original languageEnglish (US)
Title of host publicationThe Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021
PublisherAssociation for Computing Machinery, Inc
Number of pages4
ISBN (Electronic)9781450383134
StatePublished - Apr 19 2021
Event30th World Wide Web Conference, WWW 2021 - Ljubljana, Slovenia
Duration: Apr 19 2021Apr 23 2021

Publication series

NameThe Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021


Conference30th World Wide Web Conference, WWW 2021

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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