Analysis of Expert Reviews on Wines

Student: Yakovenko Yelyzaveta

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 7

Year of Graduation: 2017

Sentiment analysis is a popular technique for text classification based on polarity of a given content. The general purpose of this project is to compare different methods for sentiment analysis by applying them on the wine reviews datasets. There are classical machine learning methods such as Naive Bayes, Logistic Regression, Support Vector Machine and dictionary-based methods. In order to make a process of conducting comparative research for a variety of preprocessing steps, classification algorithms and their parameters, a library called Texch is considered. With the use of this library a binary and 3-class classification problems are solved for each of the datasets. The results show the drawbacks and strengths of different approaches and give some insights about possible future improvements.

Full text (added June 2, 2017)

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