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Wordup! At vaxxstance 2021: Combining contextual information with textual and dependency-based syntactic features for stance detection

  • Mirko Lai
  • , Alessandra Teresa Cignarella
  • , Livio Finos
  • , Andrea Sciandra

Research output: Contribution to journalConference articlepeer-review

Abstract

In this paper we describe the participation of theWordUp! 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.

Original languageEnglish
Pages (from-to)210-232
Number of pages23
JournalCEUR Workshop Proceedings
Volume2943
Publication statusPublished - 2021
Externally publishedYes
Event2021 Iberian Languages Evaluation Forum, IberLEF 2021 - Virtual, Malaga, Spain
Duration: 21 Sept 2021 → …

Keywords

  • Contextual Features
  • MDS
  • NLP
  • Network Information
  • Spanish and Basque
  • Stance Detection
  • Syntax
  • Universal Dependencies

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