Identifying Over-represented Temporal Processes in Complex Networks
نویسندگان
چکیده
Temporal networks encode interactions between entities as well as the time at which the interactions took place, allowing us to identify systematic processes within the network. We can identify subprocesses or temporal motifs that recur frequently across a large network. In this paper, we present a strategy that allows us to identify which of a given set of temporal processes are over-represented. This highlights peculiarities of behaviour in the network. Our strategy involves constructing a set of interesting temporal processes, counting their embeddings in the network through subgraph matching, and then comparing this against counts in a temporally random version of the network. The network is randomized by shu✏ing the time-stamps in the original network. We present an evaluation on data from Prosper.com, a peer-to-peer lending website. Prosper.com was closed for regulatory reasons in 2009 and our evaluation shows interesting di↵erences between the preand postclosure networks. In particular, temporal motifs indicating arbitrage are over-represented pre-closure and under-represented afterwards.
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