Do Recommender Systems Make Social Media More Susceptible to Misinformation Spreaders?

被引：13

作者：

Tommasel, Antonela ^{[1
]}

Menczer, Filippo ^{[2
]}

机构：

[1] UNCPBA, CONICET, ISISTAN, Tandil, Argentina

[2] Indiana Univ, Observ Social Media, Bloomington, IN USA

来源：

PROCEEDINGS OF THE 16TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2022 | 2022年

关键词：

link prediction; social media; misinformation; diffusion models;

D O I：

10.1145/3523227.3551473

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recommender systems are central to online information consumption and user-decision processes, as they help users find relevant information and establish newsocial relationships. However, recommenders could also (unintendedly) help propagate misinformation and increase the social influence of the spreading it. In this context, we study the impact of friend recommender systems on the social influence of misinformation spreaders on Twitter. To this end, we applied several user recommenders to a COVID-19 misinformation data collection. Then, we explore what-if scenarios to simulate changes in user misinformation spreading behaviour as an effect of the interactions in the recommended network. Our study shows that recommenders can indeed affect how misinformation spreaders interact with other users and influence them.

引用

页码：550 / 555

页数：6

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