Identifying a Review Analysis Technique for a Mobile App which analyzes customer reviews - Saluwadana S.M.R.B.; Gamage, M. (NSBM Green University, 2019)
At present due to the high competition among e-commerce companies, customer satisfaction has become a vital factor on the success of a business. Customers mainly pay attention to product or shop reviews and ratings, before purchasing a product. So, customer reviews have become a very important factor in the business. Review can be a rating or text based summary which describes their perception or experience on the shop. It is advantages for the merchants if they can get an insight about customer reviews on their business. In order to do this, identifying a review analysis technique is important. Authors used Sentiment Analysis approach which is provided by Natural Language Processing library called Natural Language Tool Kit, to analyze customer reviews which can be positive or negative. In this research authors try to find out a best fitting most accurate algorithm for completing this task. The result of this research will be used by the merchant dashboard feature of the author’s proposed cross platform mobile application, which is used to send location-based notifications to customers about promotions and offers by merchants. Through the merchant dashboard merchants are provided feedback in the form of statistical charts, summaries and recommendations to improve their business.
Keywords: Natural Language Processing; NLTK; Review Analysis; Sentiment Analysis