텍스트마이닝을 통한 댓글의 공감도 및 비공감도에 영향을 미치는 댓글의 특성 연구

• 영문명: Applying Text Mining to Identify Factors Which Affect Likes and Dislikes of Online News Comments
• 발행기관: 한국IT서비스학회
• 저자명: 김정훈(Jeong hun Kim) 송영은(Yeong eun Song) 진윤선(Yun seon Jin) 권오병(Oh byung kwon)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제14권 제2호, 159~176쪽, 전체 18쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2015.06.30

영문 초록

As a public medium and one of the big data sources that is accumulated informally and real time, online news comments or replies are considered a significant resource to understand mentalities of article readers. The comments are also being regarded as an important medium of WOM (Word of Mouse) about products, services or the enterprises. If the diffusing effect of the comments is referred to as the degrees of agreement and disagreement from an angle of WOM, figuring out which characteristics of the comments would influence the agreements or the disagreements to the comments in very early stage would be very worthwhile to establish a comment-based eWOM (electronic WOM) strategy. However, investigating the effects of the characteristics of the comments on eWOM effect has been rarely studied. According to this angle, this study aims to conduct an empirical analysis which understands the characteristics of comments that affect the numbers of agreement and disagreement, as eWOM performance, to particular news articles which address a specific product, service or enterprise per se. While extant literature has focused on the quantitative attributes of the comments which are collected by manually, this paper used text mining techniques to acquire the qualitative attributes of the comments in an automatic and cost effective manner.

목차

Abstract

1. 서론

2. eWOM으로서의 댓글

3. 온라인 뉴스 댓글의 성과에 영향을 미치는 요인

4. 텍스트마이닝

5. 결과

6. 토론 및 결론

References

키워드

eWOM Text Mining Online News Comments Online Marketing