Complex Networks 2021 - Madrid - POSTER session - ETMM: Egocentric temporal motifs miner

In this poster session, we present a novel strategy to extract statistically significant sub-graphs in temporal networks by concentrating on the egocentricity of a node. We argue that by aggregating the temporal graphs, temporal-dependent information such as the length over time of the interactions, their frequency, periodicity and others are lost. Accordingly, for each node in a three contiguous temporal graph, a structure is created, where relations within the same temporal gap maintain their structure and relations among different contiguous temporal gap exist if the node connected to the ego is the same. We report the five most frequent egocentric temporal motifs of a network representing face-to-face interactions among high school students. We also compare the discovered motifs with those discovered by a competitor.

code: https://github.com/AntonioLonga/Egocentric-Temporal-Motifs-Miner-ETMM
blog: https://antoniolonga.github.io/posts/ETMM.html
paper: https://link.springer.com/article/10.1007/s10618-021-00803-2

Видео Complex Networks 2021 - Madrid - POSTER session - ETMM: Egocentric temporal motifs miner канала Antonio Longa