Reading Stockholm Riots 2013 in social media by text-mining
This is an incremental exploratory study for researchers and policymakers interested in media phenomena during social unrest, focusing on specific data sources without broad claims.
The study tackled the problem of understanding social media's role in the 2013 Stockholm riots by analyzing Twitter and a Polish community forum using text mining and NLP, with results including identification of hot topics like Swedish Police and Politics, network analysis of popular phrases, and sentiment analysis showing negative connotations with Police.
The riots in Stockholm in May 2013 were an event that reverberated in the world media for its dimension of violence that had spread through the Swedish capital. In this study we have investigated the role of social media in creating media phenomena via text mining and natural language processing. We have focused on two channels of communication for our analysis: Twitter and Poloniainfo.se (Forum of Polish community in Sweden). Our preliminary results show some hot topics driving discussion related mostly to Swedish Police and Swedish Politics by counting word usage. Typical features for media intervention are presented. We have built networks of most popular phrases, clustered by categories (geography, media institution, etc.). Sentiment analysis shows negative connotation with Police. The aim of this preliminary exploratory quantitative study was to generate questions and hypotheses, which we could carefully follow by deeper more qualitative methods.