A classification-based approach to economic event detection in Dutch news text

Publication type
C1
Publication status
Published
Authors
Lefever, E., & Hoste, V.
Series
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC '16)
Pagination
330-335
Publisher
European Language Resources Association (ELRA)
Conference
Tenth International Conference on Language Resources and Evaluation (LREC '16) (Portoro┼ż, Slovenia)
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Abstract

Breaking news on economic events such as stock splits or mergers and acquisitions has been shown to have a substantial impact on the financial markets. As it is important to be able to automatically identify events in news items accurately and in a timely manner, we present in this paper proof-of-concept experiments for a supervised machine learning approach to economic event detection in newswire text. For this purpose, we created a corpus of Dutch financial news articles in which 10 types of company-specific economic events were annotated. We trained classifiers using various lexical, syntactic and semantic features. We obtain good results based on a basic set of shallow features, thus showing that this method is a viable approach for economic event detection in news text.