UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post’s Nesting and Syntax Information for Rumor Stance Classification
Bilal Ghanem, Alessandra Teresa Cignarella, Cristina Bosco, Paolo Rosso, Francisco Manuel Rangel Pardo
Abstract
In the present paper we describe the UPV-28-UNITO system’s submission to the RumorEval 2019 shared task. The approach we applied for addressing both the subtasks of the contest exploits both classical machine learning algorithms and word embeddings, and it is based on diverse groups of features: stylistic, lexical, emotional, sentiment, meta-structural and Twitter-based. A novel set of features that take advantage of the syntactic information in texts is moreover introduced in the paper.- Anthology ID:
- S19-2197
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1125–1131
- Language:
- URL:
- https://aclanthology.org/S19-2197
- DOI:
- 10.18653/v1/S19-2197
- Cite (ACL):
- Bilal Ghanem, Alessandra Teresa Cignarella, Cristina Bosco, Paolo Rosso, and Francisco Manuel Rangel Pardo. 2019. UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post’s Nesting and Syntax Information for Rumor Stance Classification. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1125–1131, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post’s Nesting and Syntax Information for Rumor Stance Classification (Ghanem et al., SemEval 2019)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/S19-2197.pdf