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Analysis of the Emotional Coloring of the Comments on Sites with Product Reviews and Marketplaces

Student: Ignatenko Vitaliy

Supervisor: Yury Zontov

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2019

The main goal of this task is to develop a system for analyzing the tonality of comments for websites with customer reviews. In order to accomplish this goal, during the course of the work all the tasks set earlier were performed. First of all, data on comments from the Yandex.market was obtained. On this site, comments are already divided into classes "advantages" and "disadvantages". Based on the comments received, a machine learning model was developed, defining the emotional tonality of texts using cross-validation of data. Two main methods were applied in this topic - the naive Bayes classifier and the stochastic gradient descent. Thanks to the developed methods and high-quality preprocessing of data, a model has been obtained which has a high accuracy of determining emotional coloring. The model with a probability of ~ 92% determines exactly what type of product commentary refers to - positive or negative.

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