A Novel Trust Model Based Overlapping Community Detection Algorithm for Social Networks

2020 ◽  
Vol 32 (11) ◽  
pp. 2101-2114 ◽  
Author(s):  
Shuai Ding ◽  
Zijie Yue ◽  
Shanlin Yang ◽  
Feng Niu ◽  
Youtao Zhang
Keyword(s):  
Social Networks ◽  
Community Detection ◽  
Detection Algorithm ◽  
Trust Model ◽  
Overlapping Community Detection ◽  
Model Based ◽  
Overlapping Community ◽  
Community Detection Algorithm

Overlapping Community Detection Algorithm Based on Seed Diffusion

2014 ◽  
Vol 556-562 ◽  
pp. 3300-3304 ◽  
Author(s):  
Biao Wang ◽  
Hai Bin Zheng ◽  
Ying Jue Fang ◽  
Jun Jie Wei
Keyword(s):  
Social Networks ◽  
Seed Dispersal ◽  
Community Detection ◽  
Iterative Process ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Overlapping Community Detection ◽  
Seed Node ◽  
Overlapping Community ◽  
Community Detection Algorithm

Thinking applied to the seed dispersal weighted network using node strength to find seed node, and through seed nodes for each node fitness Looking node's home societies, and update the node in the iterative process of fitness makes societies divided stabilized. The experimental results show that the network based on the weighted overlap Societies seed dispersal algorithm can be found in weighted social networks effectively divided and divided more tends to be refined.

scholarly journals Overlapping Community Detection Based on Attribute Augmented Graph

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 680
Author(s):  
Hanyang Lin ◽  
Yongzhao Zhan ◽  
Zizheng Zhao ◽  
Yuzhong Chen ◽  
Chen Dong
Keyword(s):  
Community Detection ◽  
Real World ◽  
Detection Algorithm ◽  
Overlapping Community Detection ◽  
Overlapping Communities ◽  
Adjustment Strategy ◽  
Topology Information ◽  
Overlapping Community ◽  
Real World Datasets ◽  
Community Detection Algorithm

There is a wealth of information in real-world social networks. In addition to the topology information, the vertices or edges of a social network often have attributes, with many of the overlapping vertices belonging to several communities simultaneously. It is challenging to fully utilize the additional attribute information to detect overlapping communities. In this paper, we first propose an overlapping community detection algorithm based on an augmented attribute graph. An improved weight adjustment strategy for attributes is embedded in the algorithm to help detect overlapping communities more accurately. Second, we enhance the algorithm to automatically determine the number of communities by a node-density-based fuzzy k-medoids process. Extensive experiments on both synthetic and real-world datasets demonstrate that the proposed algorithms can effectively detect overlapping communities with fewer parameters compared to the baseline methods.

Erratum: An overlapping community detection algorithm based on node distance of line graph

2019 ◽  
Vol 33 (30) ◽  
pp. 1992001
Author(s):  
Guishen Wang ◽  
Yuanwei Wang ◽  
Kaitai Wang ◽  
Zhihua Liu ◽  
Lijuan Zhang ◽  
...  
Keyword(s):  
Community Detection ◽  
Line Graph ◽  
Detection Algorithm ◽  
Overlapping Community Detection ◽  
Overlapping Community ◽  
Community Detection Algorithm
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