Abstract
Usage of internet is largely limited to passive reception of available content until the advent of large social networking websites, e.g. Facebook, Twitter, MySpace, etc. Through these websites online users create contents and build relationships with each other, amplifying users' dependence on and power of online network. This paper uses Kozinets' model of internet user segmentation to categorize users into 4 groups; collector, onlookers, VIP users, and joiners. Two differentiating factors, i.e. contributions and social capital are introduced. Unlike most studies on online networking behaviors, this study uses real behavioral data (as opposed to surveyed, subjective data) of Hao Kan Pu, a Chinese-based social network website. It is found that idle members, those having low contributions and low social capital dominate the network, accounted for 98.47% of the samples. Active members, those having high contributions and connections, are accounted only 0.21%. High-contribution members with low connections (collectors), and low-contribution members with high connections, are accounted for 0.64% and 0.67%, respectively. This structural data of online network's behavior is crucial for online social network analysis, e-marketers, as well as community development.
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Event ID
17
Paper presenter
55 411
Type of Submissions
Regular session only
Language of Presentation
English
Initial Second Choice
Weight in Programme
1 000
Status in Programme
1
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