Chengjun Wang, a second year Ph.D student, gave a talk for IR and Friends in Australia National University, May 14th.
The talk is titled Jumping over Network Threshold: News Diffusion on News Sharing Website. The rise of social media, especially the news sharing website (NSW), revives the classic study of news diffusion, and nowadays information diffusion has been extensively explored. However, there is a puzzle of limited diffusion range (Lerman et.al 2011, Bakshy et al. 2011, Leskovec et al. 2006, Sun et. al, 2009). This talk aims in gauging how widespread could news diffuse on NSW, and what’re the determinants, by introducing the concept of news sharing website (NSW) and briefly reviewing the related theories of diffusion. Drawing on the measure of threshold, this talk attempts to distinguish how news aggregating function of NSW, social influence, and homophily will influence the news diffusion on both Digg and Sina Weibo. The results reveal that: first, diffusion range on Digg is a log-normal distribution, while it follows power-law distributon on Sina Weibo; second, news jumps in the social network of Digg, and non-interpersonal effect plays an more important role in information spreading, while news infects individuals continuously on Sina Weibo (so far it’s only a conjecture). The use of epidemic models, sandpile models, and hack’s law were also briefly discussed in term of information flow system.
Aiming to encourage discussion between people working in similar fields; to provide a venue for feedback on work in progress; and to get people from different groups talking to each other, IR and Friends is a discussion group for people working in information retrieval, data mining, document computing, and similar fields.
Currently, Chengjun has been exchanging in Australia National University during February 27, 2012 – June 17, 2012. He is supervised by Robert Ackland during the exchange in ANU. Robert works at the intersection of empirical social science and computer science, developing new approaches (involving information retrieval, data visualisation and social network analysis) for studying networks on the World Wide Web. Collaborating with Rob, Chengjun is working on collecting and modeling retweeting data from Sina Weibo and Twitter.