@inproceedings{L16-1051,
 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.
},
 address = {Portorož, Slovenia},
 author = {Els Lefever and Véronique Hoste},
 booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
 month = {May},
 pages = {330--335},
 publisher = {European Language Resources Association (ELRA)},
 title = {A Classification-based Approach to Economic Event Detection in Dutch News Text},
 url = {https://www.aclweb.org/anthology/L16-1051},
 year = {2016}
}