Flavius Frasincar


2017

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COMMIT at SemEval-2017 Task 5: Ontology-based Method for Sentiment Analysis of Financial Headlines
Kim Schouten | Flavius Frasincar | Franciska de Jong
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper describes our submission to Task 5 of SemEval 2017, Fine-Grained Sentiment Analysis on Financial Microblogs and News, where we limit ourselves to performing sentiment analysis on news headlines only (track 2). The approach presented in this paper uses a Support Vector Machine to do the required regression, and besides unigrams and a sentiment tool, we use various ontology-based features. To this end we created a domain ontology that models various concepts from the financial domain. This allows us to model the sentiment of actions depending on which entity they are affecting (e.g., ‘decreasing debt’ is positive, but ‘decreasing profit’ is negative). The presented approach yielded a cosine distance of 0.6810 on the official test data, resulting in the 12th position.

2016

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COMMIT at SemEval-2016 Task 5: Sentiment Analysis with Rhetorical Structure Theory
Kim Schouten | Flavius Frasincar
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2014

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COMMIT-P1WP3: A Co-occurrence Based Approach to Aspect-Level Sentiment Analysis
Kim Schouten | Flavius Frasincar | Franciska de Jong
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)