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Under what conditions is an edge present in a social network at time t likelyto decay or persist by some future time t + Delta(t)? Previous researchaddressing this issue suggests that the network range of the people involved inthe edge, the extent to which the edge is embedded in a surrounding structure,and the age of the edge all play a role in edge decay. This paper uses weighteddata from a large-scale social network built from cell-phone calls in an 8-weekperiod to determine the importance of edge weight for the decay/persistenceprocess. In particular, we study the relative predictive power of directedweight, embeddedness, newness, and range (measured as outdegree) with respectto edge decay and assess the effectiveness with which a simple decision treeand logistic regression classifier can accurately predict whether an edge thatwas active in one time period continues to be so in a future time period. Wefind that directed edge weight, weighted reciprocity and time-dependentmeasures of edge longevity are highly predictive of whether we classify an edgeas persistent or decayed, relative to the other types of factors at the dyadand neighborhood level.

Predictors of short-term decay of cell phone contacts in a large scale communication network