scholarly journals An efficient algorithm for community detection in complex weighted networks

AIChE Journal ◽  
2021 ◽  
Author(s):  
Leila Samandari Masooleh ◽  
Jeffrey E. Arbogast ◽  
Warren D. Seider ◽  
Ulku Oktem ◽  
Masoud Soroush
Keyword(s):  
Community Detection ◽  
Efficient Algorithm ◽  
Weighted Networks ◽  
Complex Weighted Networks

scholarly journals An Efficient Algorithm for Community Detection in Complex Weighted Networks

2020 ◽  
Author(s):  
Leila Masooleh ◽  
Jeffrey Arbogast ◽  
Warren Seider ◽  
Ulku Oktem ◽  
Masoud Soroush
Keyword(s):  
Community Detection ◽  
Efficient Algorithm ◽  
Weighted Networks ◽  
Complex Weighted Networks

scholarly journals Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 443
Author(s):  
Inmaculada Gutiérrez ◽  
Juan Antonio Guevara ◽  
Daniel Gómez ◽  
Javier Castro ◽  
Rosa Espínola
Keyword(s):  
Social Networks ◽  
Community Detection ◽  
Efficient Algorithm ◽  
Fuzzy Measure ◽  
The Political ◽  
Detection Problem ◽  
Additional Information ◽  
Political Position ◽  
Networks Analysis ◽  
Polarization Capacity

In this paper, we address one of the most important topics in the field of Social Networks Analysis: the community detection problem with additional information. That additional information is modeled by a fuzzy measure that represents the risk of polarization. Particularly, we are interested in dealing with the problem of taking into account the polarization of nodes in the community detection problem. Adding this type of information to the community detection problem makes it more realistic, as a community is more likely to be defined if the corresponding elements are willing to maintain a peaceful dialogue. The polarization capacity is modeled by a fuzzy measure based on the JDJpol measure of polarization related to two poles. We also present an efficient algorithm for finding groups whose elements are no polarized. Hereafter, we work in a real case. It is a network obtained from Twitter, concerning the political position against the Spanish government taken by several influential users. We analyze how the partitions obtained change when some additional information related to how polarized that society is, is added to the problem.

A Novel Overlapping Community Detection Algorithm of Weighted Networks

2014 ◽  
Vol 599-601 ◽  
pp. 1369-1373
Author(s):  
Huang Bin You ◽  
Xue Wu Zhang ◽  
Huai Yong Fu ◽  
Zhuo Zhang ◽  
Min Li ◽  
...  
Keyword(s):  
Community Structure ◽  
Community Detection ◽  
Classification Accuracy ◽  
Time Complexity ◽  
Maximum Degree ◽  
Detection Algorithm ◽  
Overlapping Community Detection ◽  
Weighted Networks ◽  
Overlapping Community ◽  
Community Detection Algorithm

The community structure is a vital property of complex networks. As special networks the weighted networks also have community structure. Nowadays the studies of overlapping community draw attentions of researchers. However, the scale of networks become huge, so it requires the algorithm has lower time complexity and higher classification accuracy. Many existing algorithms cannot meet these two requirements at the same time. So we propose a novel overlapping community detection algorithm. Firstly we apply maximum degree node and its some special adjacent nodes as the initial community, and then expand the initial community by adding eligible nodes to it, finally other communities can be found by repeating these two steps. Experiments results show that our algorithm can detect overlapping community structure from weighted networks successfully, and also reveal that our method has higher division accuracy and lower time complexity than many previously proposed methods.

scholarly journals A comparative analysis of link removal strategies in real complex weighted networks

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
M. Bellingeri ◽  
D. Bevacqua ◽  
F. Scotognella ◽  
R. Alfieri ◽  
D. Cassi
Keyword(s):  
Comparative Analysis ◽  
Weighted Networks ◽  
Real Complex ◽  
Complex Weighted Networks
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