Natural Language Processing in Sentiment Analysis of Feedbacks

Student: Oborkin Nikolai

Faculty: St.Petersburg School of Economics and Management

Educational Programme: Big Data Analysis for Business, Economy, and Society (Master)

Year of Graduation: 2018

In this paper I have studied the methods of analysis of feedback in natural language. Data cleaning and data stamping were done, classifiers were built and used with a high degree of accuracy, and the tonality of the texts is estimated. The built-in models allow you to evaluate the feedback and predict the estimates that the client will deliver to the restaurant. Further, on the predictions obtained, was constructed model that allows searching for nonconformities using sentiment analysis of the text. Also, the provided algorithm allows you to remove reviews that cause inconsistencies and to identify abnormal reviews.

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