Predicting civil unrest by categorizing Dutch Twitter events
Amsterdam : BNAIC
InBosse, T.; Bredeweg, B. (ed.), Proceedings of the 28th Benelux Conference on Artificial Intelligence, pp. 72-79
The 28th Benelux Conference on Artificial Intelligence, 11 november 2016
Article in monograph or in proceedings
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Bosse, T.; Bredeweg, B. (ed.), Proceedings of the 28th Benelux Conference on Artificial Intelligence
SubjectLanguage & Speech Technology; Language in Society; Nederlab; The changing dynamics of news (project of: ADNEXT (Adaptive Information Extraction over Time (is project of COMIC))
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 a 'big data' problem. 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.
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