A framework of text mining approach for sentiment analysis of news articles using information agents

Author

Balasubramanian Guruswamy

Keywords and Phrases

Text mining; Balanced Scorecard

Abstract

"News articles are an important source providing information about the society. The analysis of news articles helps to measure the social importance of many events and give an understanding about current interests. In this research, the analysis of news is used as a means to recommend or suggest the news articles to the users. A sentiment analysis approach for extracting sentiments associated with positive or negative polarities is illustrated in this research project. The sentiment analysis methodology is based on a text mining technique that captures important keywords from the unstructured data such as news, distinguishes the keywords into positive or negative lexicons, ranks those keywords based on the frequency of occurrences, and recommends the news articles as positive or negative to the users. The proposed approach for sentiment analysis is illustrated with experimental results, and their main implications are discussed in this research project. This research also proposes a Balanced Scorecard framework for evaluating the performance of Information Technology (IT) projects. The Balanced Scorecard consists of four perspectives namely financial, user orientation, internal process, and learning and growth. The proposed framework of Balanced Scorecard incorporates four IT-driven performance measurement perspectives for evaluating the software agent"--Abstract, page iii.

Department(s)

Business and Information Technology

Degree Name

M.S. in Information Science and Technology

Publisher

University of Missouri--Rolla

Publication Date

Spring 2006

Pagination

ix, 92 pages

Rights

© 2006 Balasubramanian Guruswamy, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Subject Headings

Data mining
Organizational effectiveness
Text processing (Computer science)
Strategic planning

Thesis Number

T 8878

Print OCLC #

70805077

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

Recommended Citation

Guruswamy, Balasubramanian, "A framework of text mining approach for sentiment analysis of news articles using information agents" (2006). Masters Theses. 5866.
https://scholarsmine.mst.edu/masters_theses/5866