How people interact in evolving online affiliation networks
Lazaros K. Gallos, Diego Rybski, Fredrik Liljeros, Shlomo Havlin,, Hernan A. Makse

TL;DR
This paper analyzes how online affiliation networks form and evolve over time, revealing that dynamic analysis is crucial for understanding tie formation mechanisms and individual behavioral differences.
Contribution
It introduces a method to accurately estimate tie formation tendencies by tracking network evolution and uncovers sociological patterns related to individual attributes.
Findings
Time-resolved analysis improves estimation of tie formation mechanisms.
Women reciprocate connections three times more than men, especially with age.
Men prefer connecting with highly popular individuals across all ages.
Abstract
The study of human interactions is of central importance for understanding the behavior of individuals, groups and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links and we analyze quantitatively the tendencies used to create ties in these evolving online affiliation networks. We first show that an accurate estimation of these probabilistic tendencies can only be achieved by following the time evolution of the network. For example, actions that are attributed to the usual friend of a friend mechanism through a static snapshot of the network are overestimated by a factor of two. A detailed analysis of the dynamic network evolution shows that half of those triangles were generated through other mechanisms, in spite of the characteristic static pattern. We start by characterizing every single link when the tie was established in…
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