TY  - CONF
AU  - Scripps, J.
AU  - Tan, Pang-Ning
AU  - Esfahanian, A.-H.
A2  - 
T1  - Exploration of Link Structure and Community-Based Node Roles in Network Analysis
T2  - Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on
PB  - 
CY  - 
PY  - 2007/oct.
M2  - 
VL  - 
IS  - 
SP  - 649 
EP  - 654
UR  - 
M3  - 10.1109/ICDM.2007.37
KW  - roles
KW  - ambassadors
KW  - community
KW  - structure
L1  - 
SN  - 
N1  - 
N1  - 
AB  - Communities are nodes in a network that are grouped together based on a common set of properties. While the communities and link structures are often thought to be in alignment, it may not be the case when the communities are defined using other external criterion. In this paper we provide a new way to measure the alignment. We also provide a new metric that can be used to estimate the number of communities to which a node is attached. This metric, along with degree, is used to assign a community-based role to nodes. We demonstrate the usefulness of the community-based node roles by applying them to the influence maximization problem.
ER  -

TY  - CONF
AU  - Scripps, Jerry
AU  - Tan, Pang-Ning
AU  - Esfahanian, Abdol-Hossein
A2  - 
T1  - Node roles and community structure in networks
T2  - Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
PB  - ACM
CY  - New York, NY, USA
PY  - 2007/
M2  - 
VL  - 
IS  - 
SP  - 26
EP  - 35
UR  - http://doi.acm.org/10.1145/1348549.1348553
M3  - http://doi.acm.org/10.1145/1348549.1348553
KW  - roles
KW  - node
KW  - networks
KW  - loner
KW  - ambassador
KW  - conferator
KW  - bridge
KW  - social
KW  - community
KW  - network
KW  - structure
KW  - sna
KW  - bigFish
L1  - 
SN  - 978-1-59593-848-0
N1  - Node roles and community structure in networks
N1  - 
AB  - A node role is a subjective characterization of the part it plays in a network structure. Knowing the role of a node is important for many link mining applications. For example, in Web search, nodes that are deemed to be authorities on a given topic are often found to be most relevant to the user's queries. There are a number of metrics that can be used to assign roles to individual nodes in a network, including degree, closeness, and betweenness. None of these metrics, however, take into account the community structure that underlies the network. In this paper we define community-based roles that the nodes can assume (ambassadors, big fish, loners, and bridges) and show how existing link mining techniques can be improved by knowledge of such roles. A new community-based metric is introduced for estimating the number of communities linked to a node. Using this metric and a modification of degree, we show how to assign community-based roles to the nodes. We also illustrate the benefits of knowing the community-based node roles in the context of link-based classification and influence maximization.
ER  -