Analyzing characteristics of information propagation on social network graphs

Abstract

Social networking sites, such as YouTube, Flickr, Livejournal and Okrut, are becoming very popular with a large number of Internet users. As a consequence, information propagation on social network sites is becoming more important and has been studied by many researchers. However, most of the researches have been focused on statistical analysis to understand the static characteristics of social network graphs. In this paper, we will employ simulation based empirical study to better understand information diffusion process on social networking sites. According to our limited experiments, online social network graphs are more dense than the traditional social networks. It requires only three time steps to cover 90% nodes of the networks with two or three initial nodes.