Enumerating Isolated Cliques in Temporal Networks
Isolation is a concept from the world of clique enumeration that is mostly used to model communities that do not have much contact to the outside world. Herein, a clique is considered isolated if it has few edges connecting it to the rest Motivated by recent work on enumerating cliques in temporal networks, we bring the isolation concept to this setting. We discover that the addition of the time dimension leads to six distinct natural isolation concepts. Our main contribution is the development of fixed-parameter enumeration algorithms for five of these six clique types employing the parameter “degree of isolation”. On the empirical side, we implement and test these algorithms on (temporal) social network data, obtaining encouraging preliminary results.
KeywordsCommunity detection Dense subgraphs Social network analysis Time-evolving data Fixed-parameter tractability
We want to thank our student assistant Fabian Jacobs for his work on the implementation of our algorithms and anonymous reviewers for helpful feedback.