Community Detection Methods in Social Network Analysis

2014 ◽  
Vol 20 (1) ◽  
pp. 250-253 ◽  
Author(s):  
Andry Alamsyah ◽  
Budi Rahardjo ◽  
. Kuspriyanto
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Detection ◽  
Detection Methods

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.

scholarly journals Community detection and social network analysis based on the Italian wars of the 15th century

2020 ◽  
Vol 113 ◽  
pp. 25-40
Author(s):  
J. Fumanal-Idocin ◽  
A. Alonso-Betanzos ◽  
O. Cordón ◽  
H. Bustince ◽  
M. Minárová
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Detection ◽  
15Th Century ◽  
Italian Wars

scholarly journals A Social Network Analysis of Football with Complex Networks

2019 ◽  
Author(s):  
Lucas G. S. Felix ◽  
Carlos M. Barbosa ◽  
Vinícius da F. Vieira ◽  
Carolina Ribeiro Xavier
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Complex Networks ◽  
Community Detection ◽  
Soccer Players ◽  
Main Function ◽  
Transfer Data ◽  
The World ◽  
Do So

Soccer is the most popular sport in the world and due its popularity, soccer moves billions of euros over the years, in most diverse forms, such as marketing, merchandising, TV quotas and players transfers. As example, in the 2016/2017 season, only England has moved about 1.3 billion of euros only in players transfers. In this work, it is performed a study of the transfer market of player. To do so, players transfer data were gathered from the website Transfermarkt and were modeled as a graph. In order to perform this study, different Complex Networks techniques were applied, such as Overlap Community Detection and Property Analysis. Through our results we could evaluate the soccer players market, and see a pattern that every market has at least one farm country, which has a main function of selling athletes, or a buyer country, which most of its transactions is buying players.

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