TY - GEN
T1 - Discovering community-oriented roles of nodes in a social network
AU - Chou, Bin Hui
AU - Suzuki, Einoshin
PY - 2010
Y1 - 2010
N2 - We propose a new method for identifying the role of a vertex in a social network. Existing well-known metrics of node centrality such as betweenness, degree and closeness do not take the community structure within a network into consideration. Furthermore, existing proposed community-based roles are defined using cliques, and thereby it is difficult to discover vertices with only few links that bridge communities. To overcome the shortcomings, we propose three community-oriented roles, bridges, gateways and hubs, without knowledge on the community structure, for representing vertices that bridge communities. We believe that detecting the roles in a social network is useful because such nodes are valuable by themselves due to their intermediate roles between communities and also because the nodes are likely to provide a deeper understanding of the communities. Our method outperforms the state-of-the-art method through experiments using data of DBLP records in terms of the subjective validness of the outputs.
AB - We propose a new method for identifying the role of a vertex in a social network. Existing well-known metrics of node centrality such as betweenness, degree and closeness do not take the community structure within a network into consideration. Furthermore, existing proposed community-based roles are defined using cliques, and thereby it is difficult to discover vertices with only few links that bridge communities. To overcome the shortcomings, we propose three community-oriented roles, bridges, gateways and hubs, without knowledge on the community structure, for representing vertices that bridge communities. We believe that detecting the roles in a social network is useful because such nodes are valuable by themselves due to their intermediate roles between communities and also because the nodes are likely to provide a deeper understanding of the communities. Our method outperforms the state-of-the-art method through experiments using data of DBLP records in terms of the subjective validness of the outputs.
UR - http://www.scopus.com/inward/record.url?scp=78049371366&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-15105-7_5
DO - 10.1007/978-3-642-15105-7_5
M3 - Conference contribution
AN - SCOPUS:78049371366
SN - 3642151043
SN - 9783642151040
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 52
EP - 64
BT - Data Warehousing and Knowledge Discovery - 12th International Conference, DaWaK 2010, Proceedings
T2 - 12th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2010
Y2 - 30 August 2010 through 3 September 2010
ER -