Escape from an echo chamber

• Main Authors: LO, Kuan-Chieh, DAI, Shih-Chieh, XIONG, Aiping, JIANG, Jing, KU, Lun-Wei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Echo Chamber; News Stance; Social Media Bias; Web Application; Databases and Information Systems; Numerical Analysis and Scientific Computing; Social Media
• Online Access: https://ink.library.smu.edu.sg/sis_research/6949; https://ink.library.smu.edu.sg/context/sis_research/article/7952/viewcontent/3442442.3458613_pvoa_cc_by.pdf
• Institution: Singapore Management University

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.