Diffusion pattern analysis for social networking sites using small-world network multiple influence model

Despite the rapid proliferation of social networking sites (SNSs), most of the relevant research remains at the level of the analysis of their apparent characteristics. The kernel of the question, though, is the causal relationship between those characteristics and their diffusion patterns. Even though it is axiomatic that SNS diffusion patterns are highly affected by SNS characteristics, there has been little research focusing on the influence of the latter on the former. In response to this research lacuna, the present study aimed, first, to find key SNS characteristics that can be directly related to their diffusion patterns; second, to classify existing SNSs according to those derived characteristics, and finally, to examine whether the different types of SNS actually lead to distinct diffusion patterns or not. SNS diffusion patterns were analyzed using the Small-World Network Multiple Influence (SWMI) model which can explain the characteristics of social systems. The analysis results show that SNSs having a high degree of relationship extension represent a high-connection probability to users not already connected, and also, that SNSs having a high degree of shared interest have a relatively stronger external effect than other SNSs.