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ANEW for Spanish Twitter Sentiment Analysis Using Instance-Based Multi-label Learning Algorithms

  • Rodrigo PalominoEmail author
  • Carlos Meléndez
  • David Mauricio
  • Jorge Valverde-Rebaza
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 898)

Abstract

In the last years, different efforts have been made to extract information that users express through online social networking services, e.g. Twitter. Despite the progress achieved, there are still open gaps to be addressed. Related to the sentiment analysis issue, we stand out the following gaps: (a) low accuracy in sentiment classification task for short texts; and, (b) lack of tools for sentiment analysis in several languages. Aiming to fill these gaps, in this paper we apply the Spanish adaptation of ANEW (Affective Norms for English Words) as resource to improve the Twitter sentiment analysis by applying a variety of multi-label classifiers in a corpus of Spanish tweets collected by us. To the best of our knowledge, this is the first work using a Spanish adaptation of ANEW for sentiment analysis.

Keywords

Classification Sentiment analysis Multi-label classification Twitter ANEW Affective word lists 

Notes

Acknowledgements

We would like to thank psychologist María Soledad Silva for her collaboration.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rodrigo Palomino
    • 1
    Email author
  • Carlos Meléndez
    • 1
  • David Mauricio
    • 1
  • Jorge Valverde-Rebaza
    • 2
  1. 1.Universidad Peruana de Ciencias AplicadasLimaPeru
  2. 2.Department of Scientific Research, VisibiliaSão CarlosBrazil

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