earticle

논문검색

Automatic Social Media Data Extraction

초록

영어

Opinions, the key influencer of human behavior and activity is ranked as of one of the strong factors that determine the effectiveness of one’s strategy and approach in terms of influential power and trend setting capabilities. This highlights the importance of sentiment analysis done upon the extracted data. Today, statistics have shown significantly that most opinions can be obtained via many social media platforms. Social media has provided a convenient platform for web users to comfortably share their thoughts and to boldly voice up. Having to process such huge amount of data, it is proposed that automated sentiment analysis is done when extracting social media data. Using an effective algorithm which produces meaningful information from raw data, the possibilities of venturing deeper into areas like decision making and influential thinking are simply limitless.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Problem Formulation
 4. Motivation
 5. Proposed Solution
 6. Experimental Tests
 7. Conclusions
 References

저자정보

  • Estelle Xin Ying Kee School of Computing and IT, Taylor’s University, Malaysia
  • Jer Lang Hong School of Computing and IT, Taylor’s University, Malaysia

참고문헌

자료제공 : 네이버학술정보

    ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

    0개의 논문이 장바구니에 담겼습니다.