Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)

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Sentiment Analysis and product recommendation using Web Scraping and Selenium

Authors
Priyanka More1, *, Ojas Mhatre1, Om Ranade1, Devesh Patil1, Darshan Patil1
1Dept. of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India
*Corresponding author. Email: priyanka.more@viit.ac.in
Corresponding Author
Priyanka More
Available Online 22 June 2025.
DOI
10.2991/978-94-6463-738-0_27How to use a DOI?
Keywords
Sentiment Analysis; Product Recommendation; Web Scraping; Selenium; TextBlob; E-commerce; Customer Reviews; Data Visualization; Machine Learning; Natural Language Processing (NLP)
Abstract

This research explores how a product recommendation system can incorporate sentiment analysis with the help of web scraping tools such as Selenium. Its main goal is to streamline the process of collecting product ratings, evaluating customer reactions, and improving marketing tactics. The methodology is further broadened by incorporating libraries such as BeautifulSoup for parsing HTML, and TextBlob, which interprets sentiment and classifies it as favorable, unfavorable, or neutral. The analysis conducted suggests that the implementation of a sentiment analysis tool can aid in boosting sales and increasing the overall satisfaction of customers. The developed technique uses the feedbacks to integrate them into the bar graph and pie charts to showcase how the general consumers feel or perceive a given service or a product. Proper emotions are essential in e-commerce, where marketing strategies should place an emphasis on user experience, hence the need for advanced sentiment analysis tools. This paper provides a strong guideline for the businesses to redesign their product and marketing model based on the live recommendations from the consumers.

Copyright
© 2025 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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Volume Title
Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
Series
Advances in Intelligent Systems Research
Publication Date
22 June 2025
ISBN
978-94-6463-738-0
ISSN
1951-6851
DOI
10.2991/978-94-6463-738-0_27How to use a DOI?
Copyright
© 2025 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.

Cite this article

risenwbib
TY  - CONF
AU  - Priyanka More
AU  - Ojas Mhatre
AU  - Om Ranade
AU  - Devesh Patil
AU  - Darshan Patil
PY  - 2025
DA  - 2025/06/22
TI  - Sentiment Analysis and product recommendation using Web Scraping and Selenium
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 319
EP  - 334
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_27
DO  - 10.2991/978-94-6463-738-0_27
ID  - More2025
ER  -