Drug Recommendation System Based on Using NLP Algorithms to Perform Sentiment Analysis of User Reviews

DOI

10.2991/978-94-6239-713-2_9How to use a DOI?

Keywords

Sentiment Analysis; Natural Language Processing; Drug Recommendation System; User Reviews; Healthcare Decision Support

Abstract

User-generated reviews are written by people who have used medications to describe their experience. Drug reviews include descriptions of the effectiveness of the drug, side effects experienced, and the patient’s overall level of satisfaction. Although reviews of medications provide valuable real-world data, they are typically unstructured and therefore difficult to analyse manually. Existing drug recommendation systems typically rely on numerical ratings or simple filtration methods, which do not account for the detailed opinions provided in user-generated reviews. The current research seeks to create a drug recommendation system that utilises natural language processing (NLP) and sentiment analysis to analyse user reviews and generate drug recommendations. First, the system preprocesses the text of the reviews through tokenisation, stop-word elimination, and lemmatisation. The system then performs sentiment analysis using TextBlob and VADER to determine the emotional orientation of each review. Once the sentiment score has been calculated for each review, those values are aggregated to rank medications for specific medical conditions. Experimental evaluation demonstrates that the proposed approach improves sentiment classification accuracy (89% accuracy, 88% precision) and provides explainable drug recommendations. By transforming unstructured review data into structured sentiment scores, the proposed system addresses information overload and enhances the quality of healthcare decision-making.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - N. M. V. Nirmala
AU  - B. Amarnadh
AU  - B. Vasanth Naik
AU  - E. Vamsi Bharath Reddy
AU  - G. Leeladhar
PY  - 2026
DA  - 2026/06/25
TI  - Drug Recommendation System Based on Using NLP Algorithms to Perform Sentiment Analysis of User Reviews
BT  - Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)
PB  - Atlantis Press
SP  - 125
EP  - 133
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-713-2_9
DO  - 10.2991/978-94-6239-713-2_9
ID  - Nirmala2026
ER  -