Proceedings of the Conference on Bridging Engineering Disciplines with AI and Machine Learning (BEDAIML 2026)

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Sentiment Analysis of User Reviews for Swiggy and Zomato Using MHA-BiRCNN Model

Authors
Yash Agrawal1, *, Geeta Sikka1
1Department of Computer Science and Engineering, National Institute of Technology Delhi, Delhi, India
*Corresponding author. Email: 242211021@nitdelhi.ac.in
Corresponding Author
Yash Agrawal
Available Online 4 June 2026.
DOI
10.2991/978-94-6239-697-5_33How to use a DOI?
Keywords
Online food delivery services; Zomato; Swiggy; User Reviews; Google Play Store; Sentiment Analysis; Neural Network
Abstract

The online food ordering industry in India has shown growth at an impeccable pace, led by platforms like Swiggy and Zomato, that let users explore multiple restaurants, order their desired dishes, and have them delivered to their homes. Users can also post ratings and detailed comments about their experiences on the Google Play Store. The present research investigates the sentiment reflected in these user-generated reviews to uncover insights that may help improve service quality and customer satisfaction. Such opinions provide valuable understanding of consumer preferences and expectations, supporting data-driven decision-making for business growth. For this study, approximately 500,000 reviews from each application were gathered, resulting in a dataset comprising 11 distinct attributes for every review record. The data was preprocessed and analyzed with the help of MHA-BiRCNN (Multi-Head Attention – Bidirectional Recurrent Convolutional Neural Networks) model. The study showed an analysis for performance of the model and found an insight that its accuracy for Swiggy was 94.57% and Zomato was 95.35%.

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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Volume Title
Proceedings of the Conference on Bridging Engineering Disciplines with AI and Machine Learning (BEDAIML 2026)
Series
Advances in Intelligent Systems Research
Publication Date
4 June 2026
ISBN
978-94-6239-697-5
ISSN
1951-6851
DOI
10.2991/978-94-6239-697-5_33How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Yash Agrawal
AU  - Geeta Sikka
PY  - 2026
DA  - 2026/06/04
TI  - Sentiment Analysis of User Reviews for Swiggy and Zomato Using MHA-BiRCNN Model
BT  - Proceedings of the Conference on Bridging Engineering Disciplines with AI and Machine Learning (BEDAIML 2026)
PB  - Atlantis Press
SP  - 400
EP  - 409
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-697-5_33
DO  - 10.2991/978-94-6239-697-5_33
ID  - Agrawal2026
ER  -