Sentiment analysis with machine learning for drug reviews
Muhammed Oğuzhan Bozkurt, Yağız Yaman, Fahrettin Horasan · Journal of Computer & Electrical and Electronics Engineering Sciences · 2024
In the treatment of the disease, the fact that individuals use drugs independently from doctors without appropriate consultation causes their health status to become worse than normal. This article aims to conduct a sentiment analysis over the comments of individuals about the drug in case they use drugs without consultation. Within the scope of this study, patients' comments about drugs were vectorized using Bow and TF-IDF algorithms, sentiment analysis was made, and the predicted sentiments were; it was evaluated with precision, recall, f1score, accuracy and AUC score. As a result of the evaluations, the most successful result was obtained in the TF-IDF method. This result is the result of the Linear Support Vector Classifier algorithm with an Accuracy value of 93%.