We present a study of information flow that takes into account the observation that an item relevant to one person is more likely to be of interest to individuals in the same social circle than those outside of it. This is due to the fact that the similarity of node attributes in social networks decreases as a function of the graph distance. An epidemic model on a scale-free network with this property has a finite threshold, implying that the spread of information is limited. We tested our predictions by measuring the spread of messages in an organization and also by numerical experiments that take into consideration the organizational distance among individuals. This paper is sort of a follow-up to the Email as Spectroscopy paper. You can find a PowerPoint briefing on it at http://www.hpl.hp.com/shl/papers/flow/justflow.ppt Information Flow in Social Groups [PDF] | 
