Journal ArticleUnknown
Understanding Customer Sentiment: Lexical Analysis of Restaurant Reviews
Author Affiliations
Jahangirnagar University, European University of Bangladesh, University of Asia Pacific, Commonwealth Scientific and Industrial Research Organisation, ...
Published In2020 IEEE Region 10 Symposium (TENSYMP)
Year2020
Citations22
Abstract
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…
View at Publisher
BORR does not host full-text PDFs. The button above takes you to the original publisher.