From Small-World to Scale-Free Networks: What Do Real-World Network Data Tell Us?

Speaker: Alexander Nikolaev, University at Buffalo

Abstract: Online Social Network (OSN) data are hard to interpret. Many OSN users have lots of connections, easily surpassing 150 – the Dunbar number. We present a random graph formation model that explains social tie formation by bridging the gap between the Watts-Strogatz and scale free networks. It shows how the information about “talented” individuals may propagate from their friends towards the masses, with a power law in degree emerging via the mechanism fundamentally different from preferential attachment (PA): while PA assumes full visibility, our
model relies on local information exchanges. We report and interpret the model parameter estimates for several real-world networks.