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://www.aclweb.org/anthology/S19-2197
DOI:
10.18653/v1/S19-2197
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PDF:
http://aclanthology.lst.uni-saarland.de/S19-2197.pdf