#AllforJan: How Twitter Users in Europe Reacted to the Murder of Ján Kuciak—Revealing Spatiotemporal Patterns through Sentiment Analysis and Topic Modeling

Tamas Kovacs, Anna Kovacs-Györi*, Bernd Resch

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Social media platforms such as Twitter are considered a new mediator of collective action, in which various forms of civil movements unite around public posts, often using a common hashtag, thereby strengthening the movements. After 26 February 2018, the #AllforJan hashtag spread across the web when Ján Kuciak, a young journalist investigating corruption in Slovakia, and his fiancée were killed. The murder caused moral shock and mass protests in Slovakia and in several other European countries, as well. This paper investigates how this murder, and its follow-up events, were discussed on Twitter, in Europe, from 26 February to 15 March 2018. Our investigations, including spatiotemporal and sentiment analyses, combined with topic modeling, were conducted to comprehensively understand the trends and identify potential underlying factors in the escalation of the events. After a thorough data pre-processing including the extraction of spatial information from the users’ profile and the translation of non-English tweets, we clustered European countries based on the temporal patterns of tweeting activity in the analysis period and investigated how the sentiments of the tweets and the discussed topics varied over time in these clusters. Using this approach, we found that tweeting activity resonates not only with specific follow-up events, such as the funeral or the resignation of the Prime Minister, but in some cases, also with the political narrative of a given country affecting the course of discussions. Therefore, we argue that Twitter data serves as a unique and useful source of information for the analysis of such civil movements, as the analysis can reveal important patterns in terms of spatiotemporal and sentimental aspects, which may also help to understand protest escalation over space and time.
Original languageEnglish
Article number585
JournalISPRS International Journal of Geo-Information
Volume10
Issue number9
DOIs
Publication statusPublished - 31 Aug 2021

Keywords

  • social media analysis
  • sentiment analysis
  • topic modeling
  • Ján Kuciak
  • spatiotemporal clustering
  • social unrest

Fields of Science and Technology Classification 2012

  • 506 Political Science
  • 507 Human Geography, Regional Geography, Regional Planning

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