Community Detection in Heterogeneous Multi-mode Social Network via Co-training

2014 ◽  
pp. 531-538 ◽  
Author(s):  
Na Wang ◽  
Piao Chen ◽  
Xia Li
Keyword(s):  
Social Network ◽  
Community Detection ◽  
Multi Mode

Research on community detection in social network

2014 ◽  
Vol 31 (1) ◽  
pp. 35
Author(s):  
Na Wang ◽  
Xia Li ◽  
Hongying Xu
Keyword(s):  
Social Network ◽  
Community Detection

Community Detection in Social Network: An Experience with Directed Graphs

2018 ◽  
pp. 343-351
Author(s):  
Soumya Banerjee ◽  
Sumit Singh ◽  
Eiman Tamah Al-Shammari
Keyword(s):  
Social Network ◽  
Community Detection ◽  
Directed Graphs

Aspects of Various Community Detection Algorithms in Social Network Analysis

2019 ◽  
pp. 327-341
Author(s):  
Nicole Belinda Dillen ◽  
Aruna Chakraborty
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Detection ◽  
Overlapping Community Detection ◽  
Detection Algorithms ◽  
Novel Approach ◽  
Recent Developments ◽  
Overlapping Community ◽  
Related Individuals

One of the most important aspects of social network analysis is community detection, which is used to categorize related individuals in a social network into groups or communities. The approach is quite similar to graph partitioning, and in fact, most detection algorithms rely on concepts from graph theory and sociology. The aim of this chapter is to aid a novice in the field of community detection by providing a wider perspective on some of the different detection algorithms available, including the more recent developments in this field. Five popular algorithms have been studied and explained, and a recent novel approach that was proposed by the authors has also been included. The chapter concludes by highlighting areas suitable for further research, specifically targeting overlapping community detection algorithms.

Sign in / Sign up

Export Citation Format

Share Document