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