An Empirical Study Of User's Self-Disclosure Behavior On Social Network Sites

Self-disclosure on the SNS has made great contribution to relationship maintenance,social acceptance and impression management.Understanding the self-disclosure behavior on SNSs can promote the understanding of needs of SNS users,thus supporting the optimization of products and business model.This study builds a research model based on the individual characteristic-social motivation-behavior framework to interpret the self-disclosure behaviors on SNSs.The study chooses two individual characteristics(self-esteem and social anxiety)and three social motivations(self-presentation,relationship maintenance,social acceptance)to investigate the influence of three social motivations to self-disclosure,and how social motivations mediate the relationship between individual characteristics and self-disclosure.Meanwhile,this study also examined the moderating effects of gender.Results of empirical study indicate that self-presentation,relationship maintenance and social acceptance exert positive influence on self-disclosure.Moreover,self-presentation,relationship maintenance and social acceptance mediate the relationship between self-esteem and self-disclosure.However,The relationship between social anxiety and self-disclosure is insignificant,In addition,gender have significant moderating effects.Previous studies have made efforts to research self-disclosure behaviors online,but they underestimate the function of individual characteristics.This study highlights the role of self-esteem and social anxiety,and chooses three social motivations based on varieties of theoretical research to interpret the self-disclosure behavior.It provides new prospective and theoretical basis for the research about function of individual characteristics.Simultaneously,this study also has important theoretical contributions to the future research about self-disclosure.Finally,the idea and result of emphasizing essential needs also generate important management implications for SNSs operators' product optimization and service optimization.