Understanding Customer Sentiment: Lexical Analysis of Restaurant Reviews
Ara, Jinat, Hasan, Md Toufique, Al Omar, Abdullah, & Bhuiyan, Hanif (2020) Understanding Customer Sentiment: Lexical Analysis of Restaurant Reviews. In Proceedings of the 2020 IEEE Region 10 Symposium (TENSYMP). Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 295-299.
Description
Understanding customer's sentiment (satisfaction or dissatisfaction) is considered as valuable information for both the potential customers and restaurant authority. However, analyzing customer reviews (unstructured texts) one by one is a difficult task and also practically impossible when the number of reviews is enormous. Therefore, it seems conceivable to have a mechanism to analyze customer reviews automatically and provide the necessary information in a precise way. Here, we introduce a Natural Language Processing (NLP) based opinion mining methodology to analyze the customer opinion automatically. For that, first, a captive portal is used to collect customer's reviews. Then, the opinion mining technique is applied to analyze the reviews to explore customer sentiment about food quality, service, environment, etc. A data-driven experiment is conducted to evaluate the proposed methodology. The experiment result showed the effectiveness of the proposed method for retrieving and analyzing customer sentiment.
Impact and interest:
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| ID Code: | 260010 |
|---|---|
| Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) |
| Measurements or Duration: | 5 pages |
| Event Title: | IEEE Region 10 Symposium |
| Event Dates: | 2020-06-05 - 2020-06-07 |
| Event Location: | Dhaka, Bangladesh |
| Keywords: | captive portal, customer opinion, lexical analysis, opinion mining, sentiment analysis |
| DOI: | 10.1109/TENSYMP50017.2020.9230712 |
| ISBN: | 978-1-7281-7367-2 |
| Pure ID: | 201766550 |
| Divisions: | Past > QUT Faculties & Divisions > Faculty of Health Current > Research Centres > CARRS-Q Centre for Future Mobility |
| Copyright Owner: | © 2020 IEEE |
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au |
| Deposited On: | 11 Sep 2025 13:29 |
| Last Modified: | 11 Nov 2026 04:42 |
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