Formal Concept Analysis Applied to Professional Social Networks Analysis

2017 ◽  
Author(s):  
Paula R. C. Silva ◽  
Sérgio M. Dias ◽  
Wladmir C. Brandão ◽  
Mark A. Song ◽  
Luis E. Zárate
Keyword(s):  
Social Networks ◽  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Formal Concept ◽  
Social Networks Analysis ◽  
Networks Analysis

Advances in FCA-based Applications for Social Networks Analysis

2013 ◽  
Vol 1 (1) ◽  
pp. 73-89 ◽  
Author(s):  
Marie-Aude Aufaure ◽  
Bénédicte Le Grand
Keyword(s):  
Social Networks ◽  
Formal Concept Analysis ◽  
Mining Machine ◽  
Formal Concept ◽  
Social Networks Analysis ◽  
And Topology ◽  
Networks Analysis ◽  
New Applications ◽  
Web And Databases ◽  
Made In

Concept lattices have been widely used for various purposes in many different applications since the 1980s. Recent applications of Formal Concept Analysis include extensions of traditional FCA applications such as data and text mining, machine learning and knowledge management. Progress has also recently been made in software engineering, Semantic Web and databases. New applications have also emerged in the fields of healthcare, ecology, biology, agronomy, business and social networks. This article presents example of successful applications of FCA for Social Networks Analysis. We show the benefit of FCA solutions, as well as their combination with semantics and topology-based approaches. We conclude by presenting FCA-based visualization solutions and open challenges for FCA in the context of large and dynamic data.

k-Cliques mining in dynamic social networks based on triadic formal concept analysis

2016 ◽  
Vol 209 ◽  
pp. 57-66 ◽  
Author(s):  
Fei Hao ◽  
Doo-Soon Park ◽  
Geyong Min ◽  
Young-Sik Jeong ◽  
Jong-Hyuk Park
Keyword(s):  
Social Networks ◽  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Formal Concept ◽  
Dynamic Social Networks

Identification of substructures in complex networks using formal concept analysis

2018 ◽  
Vol 14 (3) ◽  
pp. 281-298 ◽  
Author(s):  
Sebastião M. Neto ◽  
Sérgio Dias ◽  
Rokia Missaoui ◽  
Luis Zárate ◽  
Mark Song
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Formal Concept Analysis ◽  
Computational Models ◽  
Behavior Pattern ◽  
Concept Analysis ◽  
Behavior Patterns ◽  
Formal Concept ◽  
Content Type ◽  
Access Patterns

Purpose In recent years, the increasing complexity of the hyper-connected world demands new approaches for social network analysis. The main challenges are to find new computational methods that allow the representation, characterization and analysis of these social networks. Nowadays, formal concept analysis (FCA) is considered an alternative to identifying conceptual structures in a social network. In this FCA-based work, this paper aims to show the potential of building computational models based on implications to represent and analyze two-mode networks. Design/methodology/approach This study proposes an approach to find three important substructures in social networks such as conservative access patterns, minimum behavior patterns and canonical access patterns. The present study approach considered as a case study a database containing the access logs of a cable internet service provider. Findings The result allows us to uncover access patterns, conservative access patterns and minimum access behavior patterns. Furthermore, through the use of implications sets, the relationships between event-type elements (websites) in two-mode networks are analyzed. This paper discusses, in a generic form, the adopted procedures that can be extended to other social networks. Originality/value A new approach is proposed for the identification of conservative behavior in two-mode networks. The proper implications needed to handle minimum behavior pattern in two-mode networks is also proposed to be analyzed. The one-item conclusion implications are easy to understand and can be more relevant to anyone looking for one particular website access pattern. Finally, a method for a canonical behavior representation in two-mode networks using a canonical set of implications (steam base), which present a minimal set of implications without loss of information, is proposed.

$K$ -Clique Community Detection in Social Networks Based on Formal Concept Analysis

2017 ◽  
Vol 11 (1) ◽  
pp. 250-259 ◽  
Author(s):  
Fei Hao ◽  
Geyong Min ◽  
Zheng Pei ◽  
Doo-Soon Park ◽  
Laurence T. Yang
Keyword(s):  
Social Networks ◽  
Community Detection ◽  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Formal Concept

Social Networks Analysis in Accounting and Finance

2019 ◽  
Author(s):  
Pietro A. Bianchi ◽  
Monika Causholli ◽  
Miguel Minutti-Meza ◽  
Raul Villamil-Otero
Keyword(s):  
Social Networks ◽  
Social Networks Analysis ◽  
Networks Analysis
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