Escape from An Echo Chamber

Companion Proceedings of the Web Conference 2021 Pub Date : 2021-04-19 DOI:10.1145/3442442.3458613

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

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引用次数: 13

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 youtube1.

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逃离回声室

回音室效应是指网民在政治问题上表现出选择性曝光和思想隔离的现象。先前的研究表明，错误信息的传播与网络回音室之间存在联系。在本文中，为了帮助用户逃离回音室，我们提出了一个新的新闻分析平台，该平台提供了不同新闻媒体来源对特定事件的立场的全景视图。此外，为了帮助用户更好地识别发布这些新闻文章的新闻来源的立场，我们采用了一个新闻立场分类模型，将他们的立场分为“同意”、“不同意”、“讨论”、“与政治立场特定事件的相关主张无关”。最后，我们提出了两种显示回声室效应的方法:1)将事件和相关新闻片段可视化;2)可视化不同政治意识形态新闻来源的新闻立场分布。通过明确回音室效应，我们预计在线用户将对特定事件有更多不同的看法。我们平台的演示视频可以在youtube1上找到。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Companion Proceedings of the Web Conference 2021

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