BibTex format
@inbook{Delvenne:2013:10.1007/978-1-4614-6729-8_11,
author = {Delvenne, J-C and Schaub, MT and Yaliraki, S and Barahona, M},
booktitle = {Dynamics On and Of Complex Networks, Volume 2},
doi = {10.1007/978-1-4614-6729-8_11},
editor = {Mukherjee and Choudhury and Peruani and Ganguly and Mitra},
pages = {221--242},
publisher = {Springer},
title = {The stability of a graph partition: A dynamics-based framework for community detection},
url = {http://dx.doi.org/10.1007/978-1-4614-6729-8_11},
year = {2013}
}
RIS format (EndNote, RefMan)
TY - CHAP
AB - Recent years have seen a surge of interest in the analysis of complexnetworks, facilitated by the availability of relational data and theincreasingly powerful computational resources that can be employed for theiranalysis. Naturally, the study of real-world systems leads to highly complexnetworks and a current challenge is to extract intelligible, simplifieddescriptions from the network in terms of relevant subgraphs, which can provideinsight into the structure and function of the overall system. Sparked by seminal work by Newman and Girvan, an interesting line of researchhas been devoted to investigating modular community structure in networks,revitalising the classic problem of graph partitioning. However, modular or community structure in networks has notoriously evadedrigorous definition. The most accepted notion of community is perhaps that of agroup of elements which exhibit a stronger level of interaction withinthemselves than with the elements outside the community. This concept hasresulted in a plethora of computational methods and heuristics for communitydetection. Nevertheless a firm theoretical understanding of most of thesemethods, in terms of how they operate and what they are supposed to detect, isstill lacking to date. Here, we will develop a dynamical perspective towards community detectionenabling us to define a measure named the stability of a graph partition. Itwill be shown that a number of previously ad-hoc defined heuristics forcommunity detection can be seen as particular cases of our method providing uswith a dynamic reinterpretation of those measures. Our dynamics-based approachthus serves as a unifying framework to gain a deeper understanding of differentaspects and problems associated with community detection and allows us topropose new dynamically-inspired criteria for community structure.
AU - Delvenne,J-C
AU - Schaub,MT
AU - Yaliraki,S
AU - Barahona,M
DO - 10.1007/978-1-4614-6729-8_11
EP - 242
PB - Springer
PY - 2013///
SN - 978-1-4614-6728-1
SP - 221
TI - The stability of a graph partition: A dynamics-based framework for community detection
T1 - Dynamics On and Of Complex Networks, Volume 2
UR - http://dx.doi.org/10.1007/978-1-4614-6729-8_11
UR - http://arxiv.org/abs/1308.1605v1
ER -
