Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{163551,
        author = {Siddhi Pusalkar and Regina Fernandes and Aishwarya Gadhave and Rohan Zanje and Atharva Sawant},
        title = {Hotel Sentiments Explored: A Deep Dive into Customer Reviews},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {11},
        pages = {1411-1415},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163551},
        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.},
        keywords = {Sentiment Analysis, BERT (Bidirectional Encoder Representation from Transformer)},
        month = {},
        }