The effects of algorithmic content selection on user engagement with news on Twitter

IF 3 3区管理学 Q1 COMMUNICATION

Information Society Pub Date : 2023-07-11 DOI:10.1080/01972243.2023.2230471

Erwan Dujeancourt, Marcel Garz

引用次数: 2

Abstract

Abstract In this article, we investigate how Twitter’s switch from a reverse-chronological timeline to algorithmic content selection in March 2016 influenced user engagement with tweets published by German newspapers. To mitigate concerns about omitted variables, we use the Facebook postings of these newspapers as a counterfactual. We find that the number of likes increased by 20% and the number of retweets by 15% within a span of 30 days after the switch. Importantly, our results indicate a rich-get-richer effect, implying that initially more popular outlets and news topics benefited the most. User engagement also increased more for sensationalist content than quality news stories.

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算法内容选择对用户参与推特新闻的影响

在本文中，我们研究了Twitter在2016年3月从逆时间顺序时间表转向算法内容选择如何影响德国报纸发布的推文的用户参与度。为了减轻对遗漏变量的担忧，我们使用这些报纸在Facebook上的帖子作为反事实。我们发现，在切换后的30天内，点赞数增加了20%，转发数增加了15%。重要的是，我们的研究结果表明了“富得更富”的效应，这意味着最初更受欢迎的媒体和新闻话题受益最大。与高质量的新闻报道相比，煽情内容的用户参与度也更高。

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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来源期刊

Information Society Multiple-

CiteScore

5.00

自引率

0.00%

发文量

期刊介绍： The Information Society is a multidisciplinary journal intended to answer questions about the Information Age. It provides a forum for thoughtful commentary and discussion of significant topics in the world of information, such as transborder data flow, regulatory issues, the impact of the information industry, information as a determinant of public and private organizational performance, and information and the sovereignty of the public and private organizational performance, and information and the sovereignty of the public. Its papers analyze information policy issues affecting society. Because of the journal"s international perspective, it will have worldwide appeal to scientists and policymakers in government, education, and industry.