지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.2
- 수록면
- 93 - 113 (21page)
- DOI
- 10.37272/JIECR.2019.02.19.1.93
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초록· 키워드
오류제보하기
Online consumer reviews have recently become one of the most important information sources of consumer experience towards products. Especially, photo images are getting more and more important as factors that provide rich and comprehensive information about products. However, few studies have explored the helpfulness of photo image itself, considering it as a unit of analysis. Therefore, this research aims to explore the antecedents affecting image helpfulness. Specifically, the effects of image factors (image category and image description) and reviewer factors (reputation, expertise, and identity disclosure) on image helpfulness were explored. For this study, we collected 1,942 image data from a restaurant review website (Yelp.com). This study adopted a negative binomial model to solve the over-dispersion problem of dependant variables. This study finds that the image factors (image with description and menu image) and reviewer factors (number of the friends, number of reviews, and real name) were identified as the influential factors that promote image helpfulness. Because this study is an initial exploratory study on image helpfulness, we believe that the framework will provide an important foundation for future image mining research work.
목차
Abstract
Ⅰ. 서론
Ⅱ. 이론적 배경
Ⅲ. 연구방법
Ⅳ. 분석결과
Ⅴ. 결론
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UCI(KEPA) : I410-ECN-0101-2019-323-000467282