Motivation Of Online Reviews:A Study Of The Relationship Between User Characteristics And Reviews

Online review is important for customers to get product information,which helps them reduce uncertainty in decision-making.However,few studies have focused on why users make comments and why there are differences in the information quality of their reviews.In order to answer these questions,user characteristics are introduced to explain the above issues.As few research related to user characteristics exists in the field of review behavior,it is a major challenge to find out their theoretical relations.This paper includes two aspects of research on user's comment intention and information quality.In study of the relationship of user characteristics and user's comment intention,this paper first relates user characteristics to the electronic word-of-mouth(eWOM)theory and proposes a theoretical model.Then,the negative binomial regression model is selected,and the online review data is used to verify the hypothesis.This study finds that longer registered customers are more willing to comment out of social influence,and customers with lower membership are more willing to comment out of the motivation of money incentives.In study of the relationship of user characteristics and information quality of comments,this paper first extracts feature words and topics from the review text data through data mining methods.Secondly,we extract information quality indicators through the “comment-feature” mapping method.Then,based on the eWOM theory and the information quality theory,a theoretical model is put forward.Finally,the fixed effects model is used to verify the theoretical hypothesis.This study finds that the comments published by customers with longer registration time have higher information quality,but the quality of the comments made by customers with lower membership are poor.This study has contributed two aspects in theory.First,this paper makes eWOM easier to be measured directly.This paper finds out the intrinsic relationship between user characteristics and eWOM,so as to infer the user's willingness to comment.Second,this paper proposes a method based on aspect classification to evaluate the information quality of comments.We extend the application of information quality theory,and further explore the reasons leading to differences in the quality of comments.From a practical point of view,with the conclusion,platforms can make more targeted strategies for specific customers,and promote them to publish more high quality comments.