Verbal Aggressions Detection in Mexican Tweets

Authors

  • Daniel Abraham Huerta-Velasco Instituto Politécnico Nacional, Centro de Investigación en Computación
  • Hiram Calvo Instituto Politécnico Nacional, Centro de Investigación en Computación

DOI:

https://doi.org/10.13053/cys-26-1-4169

Keywords:

Spanish lexical resources, sentiment analysis, mexican spanish tweets, text classification

Abstract

Verbal aggressions are a struggle that a great number of social media users have to face daily. Some users take advantage of the anonymity that social media give them and offend a person, a group of people, or a concept. The majority of proposals which pretend to detect aggressive comments on social media handle it as a classification problem. Although there are a lot of techniques to face this problem in English, there is a lack of proposals in Spanish. In this work, we propose using several Spanish lexicons which have a collection of words that have been weighted according to different criteria like affective, dimensional, and emotional values. In addition to them, estructural values, word-embeddings and one-hot codification were taken into account.

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Published

2022-03-26

Issue

Vol. 26 No. 1 (2022): Recent Advances in Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez, D. Vilariño)

Section

Articles of the Thematic Issue

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