Evolution of topics and hate speech in retweet network communities

Applied Network Science

Igor Mozetič¹  Petra Kralj Novak²  Nikola Ljubešić³  Bojan Evkoski⁴  Andraž Pelicon⁴ 

[1] Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia;Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia;Central European University, Vienna, Austria;Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia;Faculty of Information and Communication Sciences, University of Ljubljana, Ljubljana, Slovenia;Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia;Jozef Stefan International Postgraduate School, Ljubljana, Slovenia;

关键词: Twitter;    Retweet networks;    Network communities;    Community evolution;    Hate speech classification;    Topic detection;   

DOI  :  10.1007/s41109-021-00439-7

来源: Springer

【 摘 要 】

Twitter data exhibits several dimensions worth exploring: a network dimension in the form of links between the users, textual content of the tweets posted, and a temporal dimension as the time-stamped sequence of tweets and their retweets. In the paper, we combine analyses along all three dimensions: temporal evolution of retweet networks and communities, contents in terms of hate speech, and discussion topics. We apply the methods to a comprehensive set of all Slovenian tweets collected in the years 2018–2020. We find that politics and ideology are the prevailing topics despite the emergence of the Covid-19 pandemic. These two topics also attract the highest proportion of unacceptable tweets. Through time, the membership of retweet communities changes, but their topic distribution remains remarkably stable. Some retweet communities are strongly linked by external retweet influence and form super-communities. The super-community membership closely corresponds to the topic distribution: communities from the same super-community are very similar by the topic distribution, and communities from different super-communities are quite different in terms of discussion topics. However, we also find that even communities from the same super-community differ considerably in the proportion of unacceptable tweets they post.

【 授权许可】

CC BY