| Journal: | Computación y sistemas |
| Database: | |
| System number: | 000560671 |
| ISSN: | 1405-5546 |
| Authors: | Huerta Velasco, Daniel Abraham1 Calvo, Hiram1 |
| Institutions: | 1Instituto Politécnico Nacional, Centro de Investigación en Computación, México |
| Year: | 2022 |
| Season: | Ene-Mar |
| Volumen: | 26 |
| Number: | 1 |
| Pages: | 261-269 |
| Country: | México |
| Language: | Inglés |
| English 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, structural values, word embeddings and one-hot codification were taken into account. |
| Keyword: | Spanish lexical resources, Sentiment analysis, Mexican Spanish tweets, Text classification |
| Full text: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
