- ORCID iD
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0000-0001-8846-3015
- Bio (via ORCID)
- Gilles Jacobs is currently researching text mining technologies for financial applications at Ghent University. He works on artificially intelligent systems for extracting fact and opinion from economic news in the SENTiVENT project. This research integrates event extraction and aspect-based sentiment analysis methods. Before that, he worked on cyberbullying and suicidality detection in the Automated Monitoring for Cyberspace Applications (AMiCA) project. He has co-created state-of-the-art systems for sentiment analysis, automated social media moderation, and several other natural language processing applications. He holds an Advanced Master in Artificial Intelligence specializing in Speech and Language Technology. Before that, he obtained an MA in Computational and Formal Linguistics.
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- Journal Article
- A1
- open access
SENTiVENT : enabling supervised information extraction of company-specific events in economic and financial news
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Automatic classification of participant roles in cyberbullying : can we detect victims, bullies, and bystanders in social media text?
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Extracting fine-grained events and sentiment from economic news
(2021) -
Fine-grained implicit sentiment processing of polar economic events
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- Journal Article
- A1
- open access
Fine-grained implicit sentiment in financial news : uncovering hidden bulls and bears
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- Journal Article
- A1
- open access
Current limitations in cyberbullying detection : on evaluation criteria, reproducibility, and data scarcity
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- Conference Paper
- C1
- open access
Extracting fine-grained economic events from business news
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- Miscellaneous
- open access
SENTiVENT Event Annotation Guidelines v1.1
(2019) -
- Conference Paper
- C1
- open access
LT3 at SemEval-2019 Task 5 : multilingual detection of hate speech against immigrants and women in Twitter (hatEval)
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Economic event detection in company-specific news
(2018)