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Comparison of Machine Learning for Sentiment Analysis in Detecting Anxiety Based on Social Media Data
The results showed that the sentiment data amounted to 3889 and 973 in testing, and training with the greatest accuracy was the random forest with feature extraction of vectorization count and TF-IDF of 84. 99% and 82. 63%, respectively.
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