Creation of a corpus of embedded words from tweets generated in Argentina

Keywords: emotions, Twitter, natural language processing, automatic learning, word embedding

Abstract

Text processing of any kind is a task of great interest in the scientific community. One of the social networks where people frequently express themselves freely is Twitter, and therefore, it is one of the main sources for obtaining textual data. In order to perform any type of analysis, the first step is to represent the texts in a suitable way so that they can then be used by an algorithm. This paper describes the creation of a corpus of word representations obtained from Twitter using Word2Vec. Although the sets of tweets used are not massive, they are considered sufficient to take the first step in the creation of a corpus. An important contribution of this work is the training of a model that captures the idioms and colloquial expressions of Argentina, and includes emojis and hashtags within the vector space.

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Author Biography

Matías Nicolás Amor, Universidad Católica de Salta

Computer Engineer.

Professor of "Database I" of the Computer Engineering course at the Faculty of Engineering, Catholic University of Salta.

Participates in research projects on text mining and digital forensics.

Coordinator of Grupo Ideas (Group of incubation of student research work -https://ideas.ucasal.edu.ar/ ).

Published
2021-12-13
How to Cite
Talamé, M. L., Monge, A., Amor, M. N., & Cardoso, A. C. (2021). Creation of a corpus of embedded words from tweets generated in Argentina. Cuadernos De Ingeniería, 13(XIII), 07-24. https://doi.org/10.53794/ci.v13iXIII.357