Exploring The Differences Of Users' Interaction Behaviors On Microblog: The Moderating Role Of Microblogger'S Effort

On microblog, users interact with microbloggers via three behaviors-forward, comment, and like. Prior studies have paid more attention to forward, little research has investigated the differences between these three behaviors. Besides, there is a lack of an integrated theoretical framework that explores whether the same factors have different impacts on the behaviors. This study investigates the differences that users' interactions behaviors in the presence of the same factors. Building upon elaboration likelihood model (ELM) and text mining, the propose of this study is to systematically explore the relationships among content features (topical relevance, information richness) of post, source features (credibility, social ties and activeness) of microblogger, and users' interaction behaviors. More importantly, we explore whether such relationships are contingent on microblogger's effort (material motivation and information originality). A panel data was constructed using a total of 437,533 posts from Sina-Weibo, the largest microblogging platform in China. The empirical results show that topical relevance and social ties significantly affect users' interaction behaviors. Source credibility and source activeness are partially influence the behaviors. additionally, there are positive and negative effects between information richness and the behaviors, indicating that both the bright and dark side of information richness. In addition, the microblogger's effort moderate the most of the relationships between content features and the three behaviors. These results indicate that there are differences among the three behaviors. Overall, these findings could offer new insights into the deep understanding of the differences among users' interaction behaviors on microblog.