Factors Influencing Online Products Rating on Social Media: Employing Text Mining Approach

SI Ge, ZHANG Lun, ZHANG Zengyi

Chinese Journal of Journalism & Communication ›› 2015, Vol. 37 ›› Issue (6) : 38-58.

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PDF(1921 KB)
Chinese Journal of Journalism & Communication ›› 2015, Vol. 37 ›› Issue (6) : 38-58.

Factors Influencing Online Products Rating on Social Media: Employing Text Mining Approach

  • Si Ge is a graduate student at the Dept. of Journalism & Communication, University of Chinese Academy of Sciences. Email: sige12@mails.ucas.ac.cn. Zhang Lun is an assistant professor at the Dept. of Journalism & Communication, University of Chinese Academy of Sciences. Email: zhanglun@ucas.ac.cn. Zhang Zengyi is a professor at the Dept. of Journalism & Communication, University of Chinese Academy of Sciences. Email: zhzy@ucas.ac.cn.
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Abstract

User-Generated Content (UGC) is an important characteristic of social media, which advances the development of study of online information processing. Based on Uses and Gratifications Theory, this study investigates the factors that influence customers’ evaluation of products on social media. We extracted data from an online e-commerce platform (i.e., JD.com). This study found that user’s evaluation of product is determined by their using experiences of the product, user satisfaction and online social influence (i.e., other users’ comments on the product). In addition, the time period between comment and launch date of the product, the comment time (i.e., morning, afternoon, and evening), and user’ geographical location also contribute to their evaluation of the product. Moreover, the relationship between these factors and the users’ evaluation is conditional to the product type. The relationship between the factors of the users’ evaluation is significant for the search goods while insignificant for the experience goods.

Key words

social media / user-generated content / uses and gratifications theory

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SI Ge, ZHANG Lun, ZHANG Zengyi. Factors Influencing Online Products Rating on Social Media: Employing Text Mining Approach[J]. Chinese Journal of Journalism & Communication. 2015, 37(6): 38-58
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