Hotel Reviews Analysis Using Machine Learning Algorithms and Text Mining Model
DOI:
https://doi.org/10.46243/jst.2023.v8.i12.pp31-39Keywords:
Hotel Review, Text Mining, Machine Learning, Algorithms, Naive Bayes, Supervised and semi-supervised.Abstract
In the era of digital decision-making, where consumers heavily rely on online reviews, the authenticity of these reviews becomes paramount. However, the proliferation of fake reviews poses a significant challenge. In response, this study introduces and analyzes machine learning algorithms dedicated to discerning genuine feedback from deceptive ones within the context of hotel reviews and Online reviews have a significant impact on today‘s business and commerce. Decision-making for the purchase of online products mostly depends on reviews given by the users. Hence, opportunistic individuals or groups try to manipulate product reviews for their interests. This paper introduces some semi-supervised and supervised text mining models to detect fake online reviews as well as compares the efficiency of both techniques on datasets containing hotel reviews
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