Masters Theses

Author

Bo Yuan

Abstract

"With the increasing amount of text data, sentiment analysis (SA) is becoming more and more important. An automated approach is needed to parse the online reviews and comments, and analyze their sentiments. Since lexicon is the most important component in SA, enhancing the quality of lexicons will improve the efficiency and accuracy of sentiment analysis. In this research, the effect of coupling a general lexicon with a specialized lexicon (for a specific domain) and its impact on sentiment analysis was presented. Two special domains and one general domain were studied. The two special domains are the petroleum domain and the biology domain. The general domain is the social network domain. The specialized lexicon for the petroleum domain was created as part of this research. The results, as expected, show that coupling a general lexicon with a specialized lexicon improves the sentiment analysis. However, coupling a general lexicon with another general lexicon does not improve the sentiment analysis"--Abstract, page iii.

Advisor(s)

Siau, Keng, 1964-

Committee Member(s)

Nah, Fiona Fui-Hoon, 1966-
Hilgers, Michael Gene
Yin, Pei

Department(s)

Business and Information Technology

Degree Name

M.S. in Information Science and Technology

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2017

Pagination

viii, 32 pages

Note about bibliography

Includes bibliographic references (pages 27-31).

Rights

© 2017 Bo Yuan

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 11129

Electronic OCLC #

992440437

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