• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Maxim Gall
Program for Opinion Mining of Web Users Based on Machine Learning Methods
Software Engineering
(Bachelor’s programme)
2016
This paper is dedicated to using machine learning approach in opinion mining of web users.

Survey of opinion mining approaches, machine learning methods and word processing treatments used in sentiment analysis is described in this work.

The aim of the work was developing a program for opinion mining of web users. In order to achieve this goal supervised machine learning was used. Ensemble classification methods was used to perform classification nevertheless Baise classification was implemented as well on behalf of performing accuracy comparison.

By default training collection consisting of film reviews was applied to the system to construct model though it is possible to train system on any custom training set.

The paper contains 38 pages, 3 chapters, 1 illustration, 3 tables, 29 bibliography items, 5 schemes, 4 appendices.

Keywords: opinion mining, sentiment analysis, machine learning, ensemble classification

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