Reading Stockholm Riots 2013 in social media by text-mining

TL;DR

This study analyzes social media discussions during the 2013 Stockholm Riots using text mining and NLP to identify key topics, sentiment, and communication networks, providing insights into media influence and public discourse.

Contribution

It introduces a novel application of text mining and NLP to analyze social media during a major social unrest, focusing on Swedish and Polish communities.

Findings

Discussion centered on Police and Politics

Negative sentiment towards Police detected

Networks of phrases reveal key discussion categories

Abstract

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.