Regresar

Sentiment Analysis Related of International Festival of Living Arts Loja-Ecuador Employing Knowledge Discovery in Text

Abstract:

Nowadays, the use of social networks is part of the daily life of most people, especially young people, to share content and opinions. Twitter is one of the most popular social networks, in which users are the first actors to generate a large amount of information. The analysis of Twitter data requires a systematic process of collection, processing and classification. The main objective of this work is to classify the data tweets in three different classes: Positive, Negative and Neutral Opinions, corresponding to the “International Festival of the Living Arts in Loja (FIAVL)” in the years between 2016 and 2019. The official account of the “FIAVL” produced a total of 18k tweets in Spanish language, which followed the different phases of the Knowledge Discovery in Text (KDT) methodology for its analysis and study. Vector Support Machines (SVM) and Naive Bayes (NB) were used to classify the classes, where an accuracy rate of 98.7% was obtained, with the neutral opinion prevailing over the rest of the classes with 57%, thus it could be concluded that there are no positive or negative opinions about the FIAVL.