Sentiment Analysis of Online Hotel Reviews Employing Bidirectional GRU with Attention Mechanism

Title

Sentiment Analysis of Online Hotel Reviews Employing Bidirectional GRU with Attention Mechanism

Creator

Mathew M.M.; Nanjundan P.; Bashir S.

Description

Online hotel reviews are a more reliable resource for potential hotel guests. Sentiment analysis is a branch of text mining, Natural Processing Language that seeks to identify personality traits, emotions, and other factors. Deep Learning algorithms such as LSTM and GRU have successfully generated context information in sequence learning. However, deep learning cannot focus on the words that contribute the most and cannot capture important content information. This research aims to overcome the inability of LSTM and GRU to capture information. The results are satisfactory, with 93.12% accuracy, 95% ROCAUC, and 95.28% precision recall. This research paper helps managers identify areas to improve their products and services, target marketing campaigns, and identify customer churn. 2024 IEEE.

Source

ESIC 2024 - 4th International Conference on Emerging Systems and Intelligent Computing, Proceedings, pp. 237-242.

Date

2024-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

attention mechanism; BI-GRU; customer satisfaction; Online reviews; Sentiment analysis

Coverage

Mathew M.M., Christ University, Department of Data Science, Lavasa, India; Nanjundan P., Christ University, Department of Data Science, Lavasa, India; Bashir S., Christ University, Department of Data Science, Lavasa, India

Rights

Restricted Access

Relation

ISBN: 979-835034985-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ESIC60604.2024.10481617

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190984123&doi=10.1109%2fESIC60604.2024.10481617&partnerID=40&md5=44cbb2bbc324a3c0e3230b64c4724904