Proposal of a Sentiment Analysis Model in Tweets for Improvement of the Teaching - Learning Process in the Classroom Using a Corpus of Subjectivity

  • Guadalupe Gutiérrez Esparza Universidad Juárez Autónoma de Tabasco
  • Alejandro Padilla Díaz Universidad Autónoma de Aguascalientes
  • Juana Canul-Reich Universidad Juárez Autónoma de Tabasco
  • Carlos Alejandro De-Luna Universidad Politécnica de Aguascalientes
  • Julio Ponce Universidad Autónoma de Aguascalientes
Keywords: Sentiment Analysis, Naive Bayes, Corpus of Subjectivity, Twitter

Abstract

In this paper, we propose a sentiment analysis model for the assessment of teacher performance in the classroom by tweets written by a pilot group of college students. Naive Bayes (NB) is the technique to be applied to classify tweets based on the polar express emotion (positive, negative and neutral), to carry out this process, a dataset fits adding distinctive terms of context as possible features to support the classification process.

Published
2016-05-14
How to Cite
Gutiérrez Esparza, G., Padilla Díaz, A., Canul-Reich, J., De-Luna, C. A., & Ponce, J. (2016). Proposal of a Sentiment Analysis Model in Tweets for Improvement of the Teaching - Learning Process in the Classroom Using a Corpus of Subjectivity. International Journal of Combinatorial Optimization Problems and Informatics, 7(2), 22-34. Retrieved from https://ijcopi.org/ojs/article/view/37
Section
Articles