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蔼补谤迟颈肠濒别调叠别驳耻别谤颈蝉蝉别-顿铆补锄:2014:10.1098/谤蝉颈蹿.2014.0940,
author = {Beguerisse-D铆az, M and Gardu帽o-Hern谩ndez, G and Vangelov, B and Yaliraki, SN and Barahona, M},
doi = {10.1098/rsif.2014.0940},
journal = {J. R. Soc. Interface 6 December 2014},
title = {Interest communities and flow roles in directed networks: the Twitter network of the UK riots},
url = {http://dx.doi.org/10.1098/rsif.2014.0940},
volume = {11},
year = {2014}
}
TY - JOUR
AB - Directionality is a crucial ingredient in many complex networks in whichinformation, energy or influence are transmitted. In such directed networks,analysing flows (and not only the strength of connections) is crucial to revealimportant features of the network that might go undetected if the orientationof connections is ignored. We showcase here a flow-based approach for communitydetection in networks through the study of the network of the most influentialTwitter users during the 2011 riots in England. Firstly, we use directed MarkovStability to extract descriptions of the network at different levels ofcoarseness in terms of interest communities, i.e., groups of nodes within whichflows of information are contained and reinforced. Such interest communitiesreveal user groupings according to location, profession, employer, and topic.The study of flows also allows us to generate an interest distance, whichaffords a personalised view of the attention in the network as viewed from thevantage point of any given user. Secondly, we analyse the profiles of incomingand outgoing long-range flows with a combined approach of role-based similarityand the novel relaxed minimum spanning tree algorithm to reveal that the usersin the network can be classified into five roles. These flow roles go beyondthe standard leader/follower dichotomy and differ from classifications based onregular/structural equivalence. We then show that the interest communities fallinto distinct informational organigrams characterised by a different mix ofuser roles reflecting the quality of dialogue within them. Our genericframework can be used to provide insight into how flows are generated,distributed, preserved and consumed in directed networks.
AU - Beguerisse-D铆az,M
AU - Gardu帽o-Hern谩ndez,G
AU - Vangelov,B
AU - Yaliraki,SN
AU - Barahona,M
DO - 10.1098/rsif.2014.0940
PY - 2014///
TI - Interest communities and flow roles in directed networks: the Twitter network of the UK riots
T2 - J. R. Soc. Interface 6 December 2014
UR - http://dx.doi.org/10.1098/rsif.2014.0940
UR - http://arxiv.org/abs/1311.6785v2
VL - 11
ER -