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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441777" target="_blank" >RIV/00216208:11320/21:10441777 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

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

Original language description

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&apos;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.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

CEUR Workshop Proceedings

ISBN

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ISSN

1613-0073

e-ISSN

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Number of pages

23

Pages from-to

210-232

Publisher name

CEUR-WS

Place of publication

Aachen

Event location

Málaga

Event date

Sep 21, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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