@inproceedings{ghanem-etal-2019-upv,
title = "{UPV}-28-{UNITO} at {S}em{E}val-2019 Task 7: Exploiting Post{'}s Nesting and Syntax Information for Rumor Stance Classification",
author = "Ghanem, Bilal and
Cignarella, Alessandra Teresa and
Bosco, Cristina and
Rosso, Paolo and
Rangel Pardo, Francisco Manuel",
editor = "May, Jonathan and
Shutova, Ekaterina and
Herbelot, Aurelie and
Zhu, Xiaodan and
Apidianaki, Marianna and
Mohammad, Saif M.",
booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S19-2197",
doi = "10.18653/v1/S19-2197",
pages = "1125--1131",
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.",
}
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%0 Conference Proceedings
%T UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post’s Nesting and Syntax Information for Rumor Stance Classification
%A Ghanem, Bilal
%A Cignarella, Alessandra Teresa
%A Bosco, Cristina
%A Rosso, Paolo
%A Rangel Pardo, Francisco Manuel
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F ghanem-etal-2019-upv
%X 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.
%R 10.18653/v1/S19-2197
%U https://aclanthology.org/S19-2197
%U https://doi.org/10.18653/v1/S19-2197
%P 1125-1131
Markdown (Informal)
[UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post’s Nesting and Syntax Information for Rumor Stance Classification](https://aclanthology.org/S19-2197) (Ghanem et al., SemEval 2019)
ACL