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Combining Machine Learning Techniques and Natural Language Processing to Infer Emotions Using Spanish Twitter Corpus

  • Gonzalo Blázquez Gil
  • Antonio Berlanga de Jesús
  • José M. Molina Lopéz
Part of the Communications in Computer and Information Science book series (CCIS, volume 365)

Abstract

In the recent years, microblogging services, as Twitter, have become a popular tool for expressing feelings, opinions, broadcasting news, and communicating with friends. Twitter users produced more than 340 million tweets per day which may be consider a rich source of user information. We take a supervised approach to the problem, but leverage existing hashtags in Twitter for building our training data. Finally, we tested the Spanish emotional corpus applying two different machine learning algorithms for emotion identification reaching about 65% accuracy.

Keywords

Emotion Context Emotion Recognition Microblogging Twitter Features extraction Machine Learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gonzalo Blázquez Gil
    • 1
  • Antonio Berlanga de Jesús
    • 1
  • José M. Molina Lopéz
    • 1
  1. 1.Applied Artificial Intelligence GroupUniversidad Carlos III de MadridColmenarejoSpain

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