WordUp! at VaxxStance 2021: Combining Contextual Information with Textual and Dependency-Based Syntactic Features for Stance Detection.
Contributo in Atti di convegno
Data di Pubblicazione:
2021
Citazione:
WordUp! at VaxxStance 2021: Combining Contextual Information with Textual and Dependency-Based Syntactic Features for Stance Detection / Lai, Mirko; Teresa Cignarella, Alessandra; Finos, Livio; Sciandra, Andrea. - 2943:(2021), pp. 210-232. ( 2021 Iberian Languages Evaluation Forum, IberLEF 2021 Málaga (Spain) 21/09/2021).
Abstract:
In this paper we describe the participation of the WordUp! team in the VaxxStance shared task at IberLEF 2021. The goal of the competition is to determine the author's stance from tweets written both in Spanish and Basque on the topic of the Antivaxxers movement. Our approach, in the four different tracks proposed, combines the Logistic Regression classifier with diverse groups of features: stylistic, tweet-based, user-based, lexicon-based, dependency-based, and network-based. The outcomes of our experiments are in line with state-of-the-art results on other languages, proving the efficacy of combining methods derived from NLP and Network Science for detecting stance in Spanish and Basque.
Tipologia CRIS:
Relazione in Atti di Convegno
Keywords:
Stance Detection · Spanish and Basque · MDS · Contextual Features · Network Information · Syntax · Universal Dependencies · NLP
Elenco autori:
Lai, Mirko; Teresa Cignarella, Alessandra; Finos, Livio; Sciandra, Andrea
Link alla scheda completa:
Titolo del libro:
Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2021) co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2021)
Pubblicato in: