A classification-based approach to economic event detection in Dutch news text
- Publication type
- P1
- Publication status
- Published
- Authors
- Lefever, E., & Hoste, V.
- Series
- LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
- Pagination
- 330-335
- Publisher
- ELRA
- Conference
- 10th International Conference on Language Resources and Evaluation (LREC) (Portoroz, SLOVENIA)
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- (.pdf)
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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.