Resumen

HUERTA-VELASCO, Daniel Abraham  y  CALVO, Hiram. Verbal Aggressions Detection in Mexican Tweets. Comp. y Sist. [online]. 2022, vol.26, n.1, pp.261-269.  Epub 08-Ago-2022. ISSN 2007-9737.  https://doi.org/10.13053/cys-26-1-4169.

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, structural values, word embeddings and one-hot codification were taken into account.

Palabras llave : Spanish lexical resources; sentiment analysis; Mexican Spanish tweets; text classification.

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