Creation of a Sentiment Lexicon from Domain Social Media for Sentiment Analysis

Student: Voitekhovich Anna

Supervisor: Ekaterina Artemova

Educational Programme: Language Theory and Computational Linguistics (Master)

Year of Graduation: 2017

The work is devoted to creation of a sentiment lexicon for sentiment-analysis of the comments in the online-game community of the social network VK. The work provides a multidisciplinary analysis of the texts, a process of creation of a training sample, methods for identifying sentiment lexicon, the results of applying machine learning for sentiment-analysis and a rule-based approach. The statistical algorithm based on the Random Forest Classifier was improved with the help of rules based on the obtained lexicon.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses