JCEEES
Journal of Computer & Electrical and Electronics Engineering Sciences

JCEEES aims to publish original articles covering the theoretical foundations of major computer, electronic and electrical engineering sciences, as well as academic, commercial and educational aspects that propose new ideas for the application and design of artificial intelligence, software and information systems. In addition to wide-ranging regular topics, JCEEES also makes it a principle to include special topics covering specific topics in all areas of interest mainly in computational medicine, artificial intelligence, computer science, and electrical & electronic engineering science.

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Original Article
Sentiment analysis with machine learning for drug reviews
Abstract
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%.

Keywords : Drug, sentiment analysis, machine learning, natural Language processing, smote

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Article available in :
Volume 2, Issue 2, 2024
Page : 35-45
https://doi.org/10.51271/JCEEES-0016
Article Information
Received : 29 Ağu 2024
Accepted : 22 Eyl 2024
Published : 29 Eki 2024
Corresponding Author :

Fahrettin Horasan: Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Kırıkkale University, Kırıkkale, Turkiye

[email protected]
Citation : Bozkurt, M.O., Yaman, Y., & Horasan, F. (2024) Sentiment analysis with machine learning for drug reviews. J Comp Electr Electron Eng Sci, 2(2), 35-45.

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