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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.04369 |
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| _version_ | 1866913462057172992 |
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| author | Dasgupta, Subhasis Roy, Soumya Sen, Jaydip |
| author_facet | Dasgupta, Subhasis Roy, Soumya Sen, Jaydip |
| contents | In the internet era, almost every business entity is trying to have its digital footprint in digital media and other social media platforms. For these entities, word of mouse is also very important. Particularly, this is quite crucial for the hospitality sector dealing with hotels, restaurants etc. Consumers do read other consumers reviews before making final decisions. This is where it becomes very important to understand which aspects are affecting most in the minds of the consumers while giving their ratings. The current study focuses on the consumer reviews of Indian hotels to extract aspects important for final ratings. The study involves gathering data using web scraping methods, analyzing the texts using Latent Dirichlet Allocation for topic extraction and sentiment analysis for aspect-specific sentiment mapping. Finally, it incorporates Random Forest to understand the importance of the aspects in predicting the final rating of a user. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_04369 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Analyzing Consumer Reviews for Understanding Drivers of Hotels Ratings: An Indian Perspective Dasgupta, Subhasis Roy, Soumya Sen, Jaydip Computation and Language Machine Learning In the internet era, almost every business entity is trying to have its digital footprint in digital media and other social media platforms. For these entities, word of mouse is also very important. Particularly, this is quite crucial for the hospitality sector dealing with hotels, restaurants etc. Consumers do read other consumers reviews before making final decisions. This is where it becomes very important to understand which aspects are affecting most in the minds of the consumers while giving their ratings. The current study focuses on the consumer reviews of Indian hotels to extract aspects important for final ratings. The study involves gathering data using web scraping methods, analyzing the texts using Latent Dirichlet Allocation for topic extraction and sentiment analysis for aspect-specific sentiment mapping. Finally, it incorporates Random Forest to understand the importance of the aspects in predicting the final rating of a user. |
| title | Analyzing Consumer Reviews for Understanding Drivers of Hotels Ratings: An Indian Perspective |
| topic | Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2408.04369 |