Abstract
Recommender systems are central to online information consumption and user-decision processes, as they help users find relevant information and establish new social 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.
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CITATION STYLE
Tommasel, A., & Menczer, F. (2022). Do Recommender Systems Make Social Media More Susceptible to Misinformation Spreaders? In RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems (pp. 550–555). Association for Computing Machinery, Inc. https://doi.org/10.1145/3523227.3551473
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