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Analyzing Consumer Reviews for Understanding Drivers of Hotels Ratings: An Indian Perspective

arXiv 2408.04369 ↗First posted 8 Aug 2024cs.CL cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 15 references that are in the map. First posted on arXiv 8 Aug 2024.

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2 of 15 references.

References · 2

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,307

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