Veronique Hoste

NLP / finance

veronique hoste
Professor of Computational Linguistics
Ghent University

Veronique Hoste is Full Professor of Computational Linguistics at the Faculty of Arts and Philisophy at Ghent University. She is department head of the Department of Translation, Interpreting and Communication and director of the LT3 language and translation team at the same department. She holds a PhD in computational linguistics from the University of Antwerp (Belgium) on "Optimization issues in machine learning of coreference resolution" (2005). She has a strong expertise in machine learning of natural language, and more specifically in coreference resolution, word sense disambiguation, multilingual terminology extraction, classifier optimization, etc.

 

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Detecting explicit and implicit sentiment evoked by fine-grained economic news events

Abstract

While there is a rich tradition of research in event studies, the automatic detection of events remains a huge challenge which is still mainly tackled using pattern-based approaches. Furthermore, as it has been generally acknowledged that decision-making on the financial market is often influenced by emotion and other psychological factors, these events often implicitly carry a positive or negative connotation, which cannot be detected by the currently predominant explicitly lexicon-driven sentiment analysis methodologies. In this talk, I will focus on our efforts to build a corpus of over 6,200 event schemata and 12,400 sentiment tuples to enable the data-driven extraction of economic events and implicit sentiment. I will also report on our experiments with different transformer architectures tackling both tasks separately and jointly from both a coarse-grained and fine-grained perspective.  Finally, I will make an argument for the organization of a (series of) shared task(s) on financial NLP, for which our proposed corpus could be a stepping stone.