A System for Sentiment Analysis of Restaurant Reviews

Student: Kozlova Anastasiya

Supervisor: Alexey Malafeev

Faculty: Faculty of Humanities (Nizhny Novgorod)

Educational Programme: Fundamental and Applied Linguistics (Bachelor)

Year of Graduation: 2016

This paper is focused on implementation of a system for aspect-based sentiment analysis in restaurants reviews domain. A corpus of reviews has been collected and preprocessed. Frequency analysis and latent semantic analysis have been applied in order to create collections of sentiment words and aspect terms, which have been further expanded based on semantic relations and contexts of the words. Two machine learning methods (support vector machine and multinomial naive Bayes classifier) with various feature sets were implemented and tested.

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