Feature Based Opinion Mining on Hotel Reviews Using Deep Learning

Social media and networks are being used excessively these days for commenting on any news, product, services etc. We have Facebook, Twitter, LinkedIn for sharing of information with others. The data on these social media sites are in the form of text and everyday many users are commenting on these networks hence we are producing zettabytes of data each day. These data need to be managed properly so that they can be used for the benefit of companies, product manufacturers etc. The analysis of data can be done and find whether people are commenting in favor or against any particular product or service. This is known as mining of opinions. The analysis of priorities of customer’s, their needs and their attitude towards any service or product, analyzing and extracting data from reviews of customers is the primary goal of this paper. For targeting the mentioned goal, the research has focused on the approach of deep learning and NN to find the polarity of reviews of customers in the Hotel domain. Research in this dissertation explores new techniques to aggregation, automated analysis, and extraction of opinions and features of customer reviews from text by using data mining and natural language processing techniques. It focuses on aspect-based opinion mining of customer reviews from hotel booking websites. It discusses about customer reviews characteristics and describes different approaches to extract aspects and their corresponding sentiments.

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