Predicting civil unrest by categorizing Dutch twitter events

Rik van Noord*, Florian A. Kunneman, Antal van den Bosch

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


We propose a system that assigns topical labels to automatically detected events in the Twitter stream. The automatic detection and labeling of events in social media streams is challenging due to the large number and variety of messages that are posted. The early detection of future social events, specifically those associated with civil unrest, has a wide applicability in areas such as security, e-governance, and journalism. We used machine learning algorithms and encoded the social media data using a wide range of features. Experiments show a high-precision (but low-recall) performance in the first step. We designed a second step that exploits classification probabilities, boosting the recall of our category of interest, social action events.

Original languageEnglish
Title of host publicationBNAIC 2016
Subtitle of host publicationArtificial Intelligence - 28th Benelux Conference on Artificial Intelligence, Revised Selected Papers
EditorsBert Bredeweg, Tibor Bosse
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783319674674
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event28th Benelux Conference on Artificial Intelligence, BNAIC 2016 - Amsterdam, Netherlands
Duration: 10 Nov 201611 Nov 2016

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


Conference28th Benelux Conference on Artificial Intelligence, BNAIC 2016


  • Civil unrest
  • Event categorization
  • Event detection


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