@inproceedings{d9deab26a485408f9ca7b11e0884f687,
title = "Structural and regular equivalence of community detection in social networks",
abstract = "The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relative features of graphs representing in real systems is community detection. The community detection can be considered as fairly independent compartments of a graph and a similar role play. It is an important problem in the analysis of computer networks, social networks, biological networks and many other natural and artificial networks. Thus, these networks are in general very large. And the finding hidden structures and functional modules are very hard tasks. This problem is very hard and not yet satisfactorily solved. Many methods have been intended to deal with this problem in networks. Some of the most expectation are methods based on statistical inference, which support on solid mathematical foundations and return excellent results in practice. In this paper we show the blockmodeling, a collection of methods for partitioning networks according to well-specified criteria. We use the term 'blockmodeling' to characterize the usual approach to blockmodeling, which based on the concepts of structural equivalence and regular equivalence. We also gives the idea about how community is detected in social networking by Euclidean distance algorithm and REGE algorithm.",
keywords = "Block Model, Community Detection, Regular equivalence, Social Networks, Structural equivalence, Zachary Karate club network",
author = "Sovatana Hour and Li Kan",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 ; Conference date: 17-08-2014 Through 20-08-2014",
year = "2014",
month = oct,
day = "10",
doi = "10.1109/ASONAM.2014.6921679",
language = "English",
series = "ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "808--813",
editor = "Martin Ester and Guandong Xu and Xindong Wu and Xindong Wu",
booktitle = "ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining",
address = "United States",
}