Earticle

초록

영어

The Internet is one of the most widely available services in the world today. With the Internet, people are now looking for reviews on the Internet; more specifically, the social networking services. Within the social network medium, we can identify a suitable service that describes more about a person’s personality as the subject. The growth of social networking popularity has contributed to the in-crease in information available on social networking services. The flexibility of these services allows writing individual thoughts without restrictions. With the vast information available on social networking sites today, how is it possible to look all of these opinions? How do we know which opinion holds truth? How do we know if someone is not bias based on his writing? Hence, it is seen necessary to filter opinions. In this paper we look at the possibility of using search ranking as a medium of filter opinions by exploring opinion mining methods, social net-working candidates and search ranking methods. With existing sentiment analysis techniques, we can obtain opinions that are then ranked against a set of key-words.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1. Opinion Mining General Concept and Background
  2.2. Search Ranking Using Sentiment Analysis
  2.3. Decision Making Support
 3. Motivation of Using Social Network as Domain
 4. Problem Formulation
 5. Objectives
 6. Problem with Existing Techniques
  6.1. Data Extraction
  6.2. Searching and Ranking Data
 7. Proposed Solutions
  7.1. Overview
  7.2. HITS Algorithm Revisited
  7.3. Sentiment Polarity as Vector
 8. Experimental Test
 9. Conclusion
 Acknowledgement
 References

키워드

저자

• Jun Jin Choong [ School of Computing and IT, Taylor’s University, Malaysia ]
• Jer Lang Hong [ School of Computing and IT, Taylor’s University, Malaysia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605