Title :
A method for characterizing communities in dynamic attributed complex networks
Author :
Orman, Gunce Keziban ; Labatut, Vincent ; Plantevit, Marc ; Boulicaut, Jean-Francois
Author_Institution :
LIRIS, Univ. de Lyon, Lyon, France
Abstract :
Many methods have been proposed to detect communities in complex networks, but very little work has been done regarding their interpretation. In this work, we propose an efficient method to tackle this problem. We first define a sequence-based representation of networks, combining temporal information, topological measures and nodal attributes. We then describe how to identify the most emerging sequential patterns of this dataset and use them to characterize the communities. We also show how to highlight outliers. Finally, as an illustration, we apply our method to a network of scientific collaborations.
Keywords :
algorithm theory; complex networks; topology; dynamic attributed complex networks; nodal attributes; scientific collaborations; sequence-based representation; temporal information; topological measures; Communities; Complex networks; Complexity theory; Conferences; Itemsets; Social network services; Community Interpretation; Dynamic Attributed Networks; Topological Measures;
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on
Conference_Location :
Beijing
DOI :
10.1109/ASONAM.2014.6921629