Hotel Sentiments Explored: A Deep Dive into Customer Reviews

Hotel Sentiments Explored: A Deep Dive into Customer Reviews
Author(s):
Siddhi Pusalkar, Regina Fernandes, Aishwarya Gadhave, Rohan Zanje, Atharva Sawant
Keywords:
Sentiment Analysis, BERT (Bidirectional Encoder Representation from Transformer)
Abstract
Sentiment Analysis is a machine learning technique designed to interpret human emotions. By enabling machines to comprehend and extract insights from emotions, it becomes a valuable resource for business growth and development. Hotel reviews gathered from guests can be categorized as positive, negative, or neutral, allowing for sentiment analysis. This concise analysis of reviews is crucial for maintaining quality control in hotel services. This project adopts an advanced approach to extracting insights from hotel reviews by leveraging various machine learning algorithms along with BERT (Bidirectional Encoder Representations from Transformers), a cutting-edge natural language processing model. In today's digital era, where online reviews significantly impact consumer decisions, this project aims to innovate how the hospitality industry perceives and responds to customer sentiments, ultimately enhancing guest experiences and overall satisfaction.
Article Details
Unique Paper ID: 163551 Publication Volume & Issue: Volume 10, Issue 11 Page(s): 1411 - 1415
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