Individual Neighbourhood Exploration in Complex Multi-layered Social Network

Social networks can be extracted from different data about communication or common activities in organizations, companies or various Internet-based services. Different types of data processed may result in creation of separate layers in the complex multilayered social network. Analysis of neighbourh...

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Bibliographic Details
Main Authors: Kazienko, Przemyslaw, Brodka, Piotr, Musial, Katarzyna
Format: Conference Proceeding
Language:English
Subjects:
Communication channels
Complex networks
Cross layer design
Fitting
Mathematics of computing
Mathematics of computing > Discrete mathematics
Mathematics of computing > Discrete mathematics > Graph theory
Mathematics of computing > Discrete mathematics > Graph theory > Network flows
Measurement
multi-layered social network
neighbourhood analysis
Presses
social network analysis
Social network services
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Summary:Social networks can be extracted from different data about communication or common activities in organizations, companies or various Internet-based services. Different types of data processed may result in creation of separate layers in the complex multilayered social network. Analysis of neighbourhoods of network members and their utilization to social group discovery appears to be an interesting and important research domain. Since there is no measure to evaluate structure of the neighbourhoods in the multilayered social network, a new measure called cross layered multi-layered clustering coefficient (CLMCC) is proposed in the paper. It enables to analyse the density of mutual connections of neighbours that occur in at least a given number of layers in a social network. Additionally, experimental studies on real world data are presented.
DOI:10.1109/WI-IAT.2010.313