2024
DOI: 10.31127/tuje.1352481
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Sentiment analysis of coronavirus data with ensemble and machine learning methods

Muhammet Sinan Başarslan,
Fatih Kayaalp

Abstract: The coronavirus pandemic has distanced people from social life and increased the use of social media. People's emotions can be determined with text data collected from social media applications. This is used in many fields, especially in commerce. This study aims to predict people's sentiments about the pandemic by applying sentiment analysis to Twitter tweets about the pandemic using single machine learning classifiers (Decision Tree-DT, K-Nearest Neighbor-KNN, Logistic Regression-LR, Naïve Bayes-NB, Random F… Show more

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