Opinion analysis of COVID-19 tweets generated by Ecuadorian users

Authors

  • John A. Torres A. Carrera de Ingeniería en Sistemas/Computación, Universidad Nacional de Loja, Loja, Ecuador

Keywords:

Opinion Analysis, KDD, Text mining, Processing Natural Language

Abstract

Currently, millions of data are generated through the social network Twitter. The analysis of this data is fundamental and important to examine and investigate the knowledge that is hidden among them. In this research work, an opinion analysis of tweets generated in Ecuador related to COVID-19 in the year 2020 is carried out. For this purpose, the Knowledge Discovery in Databases (KDD) methodology was used for data management and for the discovery of hidden patterns in the dataset that has a total of 149,077 tweets. Several tools were used for Natural Language Processing, such as MeaningCloud, TextBlob, IBM Watson, Bayesian Algorithm (Own Creation), Google Cloud Natural Language. The generated clusters presented the following polarity: 84,044 positive tweets, 52,451 negative tweets and 12,582 neutral tweets.

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Published

2021-07-15

How to Cite

Torres A., J. A. (2021). Opinion analysis of COVID-19 tweets generated by Ecuadorian users. CEDAMAZ, 11(1), 70–77. Retrieved from https://revistas.unl.edu.ec/index.php/cedamaz/article/view/1039

Issue

Vol. 11 No. 1 (2021): CEDAMAZ

Section

Ciencias exactas e ingenierías

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