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

被引：10

作者：

Dujeancourt, Erwan ^{[1
,2
,3
]}

Garz, Marcel ^{[1
,2
]}

机构：

[1] Jonkoping Univ, Ctr Entrepreneurship & Spatial Econ, Jonkoping Int Business Sch, Jonkoping, Sweden

[2] Jonkoping Univ, Media Management & Transformat Ctr, Jonkoping Int Business Sch, Jonkoping, Sweden

[3] Jonkoping Univ, Jonkoping Int Business Sch, Gjuterigatan 5, S-55111 Jonkoping, Sweden

来源：

INFORMATION SOCIETY | 2023年 / 39卷 / 05期

关键词：

Algorithm bias; Facebook; news quality; social media; ONLINE SOCIAL NETWORKS; IMPACT; CONSUMPTION; OPINION; BIAS;

D O I：

10.1080/01972243.2023.2230471

中图分类号：

G2 [信息与知识传播];

学科分类号：

05 ; 0503 ;

摘要：

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.

引用

页码：263 / 281

页数：19

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