SENTIMENT ANALYSIS ABOUT BIDDING IN TWITTER® POSTS MADE DURING THE PANDEMIC PERIOD
DOI:
https://doi.org/10.48090/ciki.v1i1.1021Keywords:
sentiment analysis, . social networks, public purchases, machine learningAbstract
Computerized social networks have become an environment in which the population expresses their concerns, due to the tools with greater autonomy and reverberation of their speeches. In 2020, with the COVID-19 pandemic, these characteristics were enhanced. In this experiment, the social network Twitter® was used as a tool to measure the feeling of the Brazilian population about public purchases carried out during the aforementioned period. With a random base of 957 tweets for the classification task, divided into two groups: training and testing. The model included a pre-processing step in which repeated tweets posted by bot or fake users were eliminated. Three predictive algorithms were evaluated: Logistic Regression, Neural Networks and Random Forest. The Logistic Regression algorithm had the best performance with 0.777 accuracy.
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