5 research outputs found
Importance of individual events in temporal networks
Records of time-stamped social interactions between pairs of individuals
(e.g., face-to-face conversations, e-mail exchanges, and phone calls)
constitute a so-called temporal network. A remarkable difference between
temporal networks and conventional static networks is that time-stamped events
rather than links are the unit elements generating the collective behavior of
nodes. We propose an importance measure for single interaction events. By
generalizing the concept of the advance of event proposed by [Kossinets G,
Kleinberg J, and Watts D J (2008) Proceeding of the 14th ACM SIGKDD
International conference on knowledge discovery and data mining, p 435], we
propose that an event is central when it carries new information about others
to the two nodes involved in the event. We find that the proposed measure
properly quantifies the importance of events in connecting nodes along
time-ordered paths. Because of strong heterogeneity in the importance of events
present in real data, a small fraction of highly important events is necessary
and sufficient to sustain the connectivity of temporal networks. Nevertheless,
in contrast to the behavior of scale-free networks against link removal, this
property mainly results from bursty activity patterns and not heterogeneous
degree distributions.Comment: 36 pages, 13 figures, 2 table