The effect of toxicity on COVID-19 news network formation in political subcommunities on Reddit: An affiliation network approach

作者：

Highlights：

• COVID-19 news sources cluster into five communities: mainstream, international, right-wing, scientific, and left-wing.

• Right-wing sources are associated with the highest toxicity, and scientific sources with the least toxicity.

• Sources associated with highly toxic content are more popular than those associated with lowly toxic content.

• Sources with similar levels of toxicity are shared often in the same political subcommunities.

• Implication: social media platforms should algorithmically promote scientific sources to encourage non-combative rhetoric in fighting the COVID-19 pandemic.

摘要

•COVID-19 news sources cluster into five communities: mainstream, international, right-wing, scientific, and left-wing.•Right-wing sources are associated with the highest toxicity, and scientific sources with the least toxicity.•Sources associated with highly toxic content are more popular than those associated with lowly toxic content.•Sources with similar levels of toxicity are shared often in the same political subcommunities.•Implication: social media platforms should algorithmically promote scientific sources to encourage non-combative rhetoric in fighting the COVID-19 pandemic.

论文关键词：Social media,Affiliation networks,Political polarization,Exponential random graph modeling,Toxicity,News sharing

论文评审过程：Received 21 October 2020, Revised 26 July 2021, Accepted 29 July 2021, Available online 9 August 2021, Version of Record 9 August 2021.

论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2021.102397