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Actions Towards Social Networking Sites

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Actions Towards Social Networking Sites
FACEBOOK ME: COLLECTIVE SELF-ESTEEM, NEED TO BELONG,AND INTERNET SELF-EFFICACY AS PREDICTORS OF THE IGENERATION'S ATTITUDES TOWARD SOCIAL NETWORKING SITES
Harsha Gangadharbatla
ABSTRACT: Within the user-generated content sites, the role and growth of social networking sites has been undeniably overwhelming. Social networking sites (SNS) generate millions of dollars in revenue and advertising, yet little is known about why college students join and participate in these sites, which allow users to create their own content or space. This study adopts survey methodology to investigate the influence of college students' level of Internet self-efficacy, need to belong, need for cognition, and collective self-esteem on their attitude toward SNS. Internet self-efficacy, need to belong, and collective self-esteem all have positive effects on attitudes toward SNS. Furthermore, attitude toward SNS mediates the relationship between willingness to join SNS and (1) Internet self-efficacy and (2) need to belong, and the mediation is only partial between willingness to join and collective self-esteem. The author also draws managerial implications.

User-generated content sites provide platforms for information sharing, video sharing, photo sharing, and blogging. Often referred to as Web 2.0, these sites are expected to generated $4.3 billion by 2011, more than four times what U.S. user-generated content sites generated in 2007 when more than 70 million U.S. Internet users created content online (eMarketer 2006). According to Nielsen/NetRatings, user-generated content sites constitute 5 out of top 10 fastest growing Web brands (Neilsen 2006). Among these usergenerated content sites, the role and growth of social networking sites (SNS) has been undeniably overwhelming, especially among teens and young adults; more than 55% of teens online use social networks, and 48% of them visit SNS daily or more (Lenhart and Madden 2007). Despite these staggering statistics, very little

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