Auditing Entertainment Traps on YouTube: How Do Recommendation Algorithms Pull Users Away from News

IF 4.6 1区社会学 Q1 COMMUNICATION

Political Communication Pub Date : 2024-04-19 DOI:10.1080/10584609.2024.2343769

Shengchun Huang, Tian Yang

引用次数: 0

Abstract

Recommendation algorithms that customize information feeds for individuals have raised concerns about exacerbating inequalities in news exposure among citizens. In response to these concerns, we co...

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审计 YouTube 上的娱乐陷阱：推荐算法如何让用户远离新闻

为个人定制信息源的推荐算法引发了人们对加剧公民新闻接触不平等的担忧。为了回应这些担忧，我们共同开发了一种...

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来源期刊

Political Communication Multiple-

CiteScore

13.90

自引率

2.70%

发文量

期刊介绍： Political Communication is a quarterly international journal showcasing state-of-the-art, theory-driven empirical research at the nexus of politics and communication. Its broad scope addresses swiftly evolving dynamics and urgent policy considerations globally. The journal embraces diverse research methodologies and analytical perspectives aimed at advancing comprehension of political communication practices, processes, content, effects, and policy implications. Regular symposium issues delve deeply into key thematic areas.