TY - GEN
T1 - Escape from An Echo Chamber
AU - Lo, Kuan Chieh
AU - Dai, Shih Chieh
AU - Xiong, Aiping
AU - Jiang, Jing
AU - Ku, Lun Wei
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/6
Y1 - 2021/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85107688796&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107688796&partnerID=8YFLogxK
U2 - 10.1145/3442442.3458613
DO - 10.1145/3442442.3458613
M3 - Conference contribution
AN - SCOPUS:85107688796
T3 - The Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021
SP - 713
EP - 716
BT - The Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021
PB - Association for Computing Machinery, Inc
T2 - 30th World Wide Web Conference, WWW 2021
Y2 - 19 April 2021 through 23 April 2021
ER -