Sentiment Analysis on Monolingual, Multilingual and Code-Switching Twitter Corpora

  1. David Vilares 1
  2. Miguel A. Alonso 1
  3. Carlos Gómez-Rodríguez 1
  1. 1 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

Libro:
6th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis WASSA 2015: Workshop Proceedings : 17 September 2015 Lisboa, Portugal
  1. Alexandra Balahur (ed. lit.)
  2. Erik van der Goot (ed. lit.)
  3. Piek Vossen (ed. lit.)
  4. Andres Montoyo (ed. lit.)

Editorial: The Association for Computational Linguistics

ISBN: 978-1-941643-32-7

Año de publicación: 2015

Páginas: 2-8

Congreso: Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (6. 2015. Lisboa)

Tipo: Aportación congreso

DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

We address the problem of performing polarity classification on Twitter over different languages, focusing on English and Spanish, comparing three techniques: (1) a monolingual model which knows the language in which the opinion is written, (2) a monolingual model that acts based on the decision provided by a language identification tool and (3) a multilingual model trained on a multilingual dataset that does not need any language recognition step. Results show that multilingual models are even able to outperform the monolingual models on some monolingual sets. We introduce the first code-switching corpus with sentiment labels, showing the robustness of a multilingual approach.

Fuente de los datos: Dialnet