Entropy-based Social Network Link Partition Algorithm

DOI

10.2991/aeecs-18.2018.41How to use a DOI?

Keywords

Social computing, Social networks, Community division, ELP algorithm

Abstract

It is an important core issue in social networks to divide community or group. And, the network node is the mainstream of community division algorithm as the processing object to divide the network. This paper introduces the entropy theory into social networks partition on the basic of studying the concept of entropy and social networks partition algorithm. And we proposed an Entropy-based Link Partition algorithm (ELP algorithm), which is the social network links as the processing object. Also, the similarity between two objects is properly defined and improved, which thus is more close to the real situation of the social network. Experimentation on two real-world networks, and we obtained results of community division and compared with other community partition algorithms to verify the effectiveness of the proposed algorithm. The ELP algorithm has a higher accuracy, and communities are more realistic than that generated by either of the Link Clustering algorithm (LC) or the classical Clique Percolation Method (CMP).

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shusen Zhang
AU  - Xun Liang
AU  - Xiaoping Zhou
AU  - Xuan Zhang
PY  - 2018/03
DA  - 2018/03
TI  - Entropy-based Social Network Link Partition Algorithm
BT  - Proceedings of the 2018 2nd International Conference on Advances in Energy, Environment and Chemical Science (AEECS 2018)
PB  - Atlantis Press
SP  - 234
EP  - 242
SN  - 2352-5401
UR  - https://doi.org/10.2991/aeecs-18.2018.41
DO  - 10.2991/aeecs-18.2018.41
ID  - Zhang2018/03
ER  -