Gratifications of using Facebook, Twitter, Instagram, or Snapchat to follow Brands
Phua, Joe, Seunga Venus Jin, & Jihoon (Jay) Kim (Grady PhD student) (2017). Gratifications of using Facebook, Twitter, Instagram, or Snapchat to follow Brands: The Moderating Effect of Social Comparison, Trust, Tie Strength, and Network Homophily on Brand Identification, Brand Engagement, Brand Commitment, and Membership Intention. Telematics and Informatics, 34(1), 412-424.
[2015 Impact Factor: 2.261]
Abstract: Applying uses and gratifications theory (UGT), this study examined consumers’ use of one of four social networking sites (SNSs): Facebook, Twitter, Instagram, or Snapchat, for following brands, and their influence on brand community-related outcomes. Results (N = 297) indicated Snapchat users scored highest for passing time, sharing problems, and improving social knowledge, while Instagram users scored highest for showing affection, following fashion, and demonstrating sociability. Twitter users had highest brand community identification and membership intention, while Instagram users had highest brand community engagement and commitment. Attention to social comparison, SNS trust, tie strength, and homophily also significantly moderated the relationship between frequent use of each SNS to follow brands, and brand community-related outcomes. Implications for future research on SNS users’ goal-directed consumption behaviors are discussed.
Abstract: Participants (N=88) in a two-condition (Facebook post information level: high vs. low) mixed factorial design took part in a laboratory experiment that utilized eye tracking to gauge what areas of the page in common news layouts attract viewers’ gaze, and whether this viewing amount of information about the story disclosed in the Facebook posts. […]
Bartosz WojdynskiCamila EspinaKate KeibJennifer MalsonHyejin BangYen-I Lee
A Social Networks Approach to Online Social Movement:
Abstract: The movement to free Al Jazeera journalists (#FreeAJStaff), imprisoned by Egyptian authorities, utilized Twitter over almost two years, between 2014 and 2015. This study applied a social networks approach to study patterns of information flow, social mediators, and clusters, formed by the #FreeAJStaff movement on Twitter.Analysis of 22 months of data found social mediators […]