Reviews on Group Detection in Online Social Networks

PAN Li; WU Peng; HUANG Danhua

doi:10.11999/JEIT161192

Volume 39 Issue 9

Sep. 2017

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PAN Li, WU Peng, HUANG Danhua. Reviews on Group Detection in Online Social Networks[J]. Journal of Electronics & Information Technology, 2017, 39(9): 2097-2107. doi: 10.11999/JEIT161192

Citation:

PAN Li, WU Peng, HUANG Danhua. Reviews on Group Detection in Online Social Networks[J]. Journal of Electronics & Information Technology, 2017, 39(9): 2097-2107. doi: 10.11999/JEIT161192

PAN Li, WU Peng, HUANG Danhua. Reviews on Group Detection in Online Social Networks[J]. Journal of Electronics & Information Technology, 2017, 39(9): 2097-2107. doi: 10.11999/JEIT161192

Citation:

PAN Li, WU Peng, HUANG Danhua. Reviews on Group Detection in Online Social Networks[J]. Journal of Electronics & Information Technology, 2017, 39(9): 2097-2107. doi: 10.11999/JEIT161192

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Reviews on Group Detection in Online Social Networks

doi: 10.11999/JEIT161192

Funds:

The National Natural Science Foundation of China (U1636105), The National 973 Program of China (2013CB 329603)

Received Date: 2016-11-04
Rev Recd Date: 2017-02-26
Publish Date: 2017-09-19

Abstract

Abstract

Groups are important mesoscopic organizations of Online Social Networks (OSNs). Group detection not only has important theoretical significance, but also has a wide range of applications. It promotes the application and development of online social networks. In this paper, group detection technology in online social networks is studied. Based on analyzing the formation mechanism of social groups, the online social network groups is defined and the group detection problem is introduced. According to different features adopted by group detection methods, the methods based on the attribute features only and those based on combination of attribute features and structure features are analyzed, respectively. Especially, it reviews the malicious behavior group detection methods by analyzing their feature selection mechanisms and detection models in detail. Finally, further research direction of group detection in online social networks is prospected.
- Online Social Networks (OSN),
- Group detection,
- Malicious behavior group

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References(72)

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