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Analysis of Texts Based on Methods of Machine Learning

Student: Ershova Aleksandra

Supervisor: Timofey Shevgunov

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Master)

Year of Graduation: 2019

In the modern world people create an immense amount of information through such social media as Twitter, Facebook, Instagram. Due to the enormous growth of information volumes on the Internet, unsystematic research of the vast amounts of this data has become practically impossible. Therefore, emotion and sentiment analysis has become an essential topic nowadays. In this work the problem of sentiment analysis inTwitter using machine learning techniques was addressed. The aim of the research was to create an application and find a suitable algorithm which would help to predict whether a certain tweet has positive or negative with high accuracy. The result of this work is an application, which purpose is to detect sentiments of a certain tweet. In order to create an application which is able to predict tweet's sentiments, different combinations of vectorization processes and classifiers were evaluated. The result of the project is an application, which consists a classifier with accuracy more than 90%. Developed application can be used by different organizations in order to improve products attributes according to customer needs and retrieve other business insights.

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