Conference Proceedings
Studying the temporal dynamics of word co-occurrences: An application to event detection
D Preotiuc-Pietro, SPN Kusumam, M Hepple, T Cohn, N Calzolari (ed.), K Choukri (ed.), T Declerck (ed.), S Goggi (ed.), M Grobelnik (ed.), B Maegaard (ed.), J Mariani (ed.), H Mazo (ed.), A Moreno (ed.), J Odijk (ed.), S Piperidis (ed.)
Proceedings of the 10th edition of the Language Resources and Evaluation Conference (LREC) | European Language Resources Association | Published : 2016
Open access
Abstract
Streaming media provides a number of unique challenges for computational linguistics. This paper studies the temporal variation in word co-occurrence statistics, with application to event detection. We develop a spectral clustering approach to find groups of mutually informative terms occurring in discrete time frames. Experiments on large datasets of tweets show that these groups identify key real world events as they occur in time, despite no explicit supervision. The performance of our method rivals state-of-the-art methods for event detection on F-score, obtaining higher recall at the expense of precision.
Grants
Awarded by European Commission