Understanding Social Networks Using Formal Concept Analysis

Snášel, Václav; Horák, Zdeněk; Abraham, Ajith

doi:10.1109/wiiat.2008.74

Cited by 21 publications

(6 citation statements)

References 8 publications

(8 reference statements)

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“…In [7] it is demonstrated that formal concept analysis can be used to facilitate the identification and representation of a behavior in a social network, using concept lattices.…”

Section: Related Workmentioning

confidence: 99%

Canonical Computational Models Based on Formal Concept Analysis for Social Network Analysis and Representation

Resende

Moraes

Dias

et al. 2015

2015 IEEE International Conference on Web Services

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Formal concept analysis is a mathematics research field introduced in the beginning of the 1980s by Rudolf Wille, that has been applied in several different knowledge areas, including Computer Science. FCA is a data analysis theory that identifies conceptual structures within data sets or formal contexts. In this work, we propose an FCA-based approach to build minimal implication rules-based computational models for social networks. As an application example, in this work we constructed canonical models using data extracted from user sessions in one of the most popular social networks in Brazil, Orkut. These models represent the patterns of access to Orkut, about a certain problem domain, and are composed by a minimal rule set.

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“…In [7] it is demonstrated that formal concept analysis can be used to facilitate the identification and representation of a behavior in a social network, using concept lattices.…”

Section: Related Workmentioning

confidence: 99%

Canonical Computational Models Based on Formal Concept Analysis for Social Network Analysis and Representation

Resende

Moraes

Dias

et al. 2015

2015 IEEE International Conference on Web Services

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“…The tools might also include such components as fuzzy logic and probabilistic analysis (for predictive analysis, trends and situation assessment) (Kim & Bishu, 2006;PR-OWL, 2012), Conceptual Graphs for (Criminal) Transaction Modelling (identification of key agents, resources and facilitators for SOEC) (Jedrzejek, Falkowski, & Bak, 2009;Du, Song, & Munro, 2006;Mifflin, Boner, Godfrey, & Skokan, 2004), Formal Concept Analysis (FCA) for pattern finding (modus operandi and indicator analysis, threat detection, taxonomy visualisation, predictive analysis) (Snášel, Horák, & Abraham, 2008;Kirda, 2010;Thonnard, 2011), Social Network Analysis (SNA) (for the detection and analysis of OC groups and OC activity) (McNally & Alston, 2006;Fox, 2012;SAS, 2009), extending SNA with FCA: Formal Conceptual Network Analysis (to provide SNA with enhanced capabilities for analysis of OC group-group interaction and OC hierarchies, extending CGs with FCA: CG-FCA (identification of incomplete transactions, supply chains and transactional hierarchies, identification of missing agents in transitions) as described earlier (Andrews & Polovina, 2011), linked data analysis (for detecting financial pathways and supply and economic food chains) (Larreina, 2007), Fuzzy Cognitive Mapping (FCM) (for determining weighted cause-and-effect relations and actions) (Carvalho & Tomè, 1999) and Machine Learning (for diagnostic analysis of suspected SOEC activity and economic impact) (Schrodt, 1995).…”

Section: The E-puems Tool-kitmentioning

confidence: 99%

Implementation and Visualization of Conceptual Graphs in CharGer

Delugach

2014

International Journal of Conceptual Structures and Smart Applications

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Practitioners using conceptual graphs are naturally interested in tools that support its features. The CharGer editing software has been available for many years, giving the community a chance to evaluate and contribute to CharGer's ever-expanding capabilities. As result of that experience, the author discusses a few lessons learned about visualization and implementation of conceptual graphs. Features such as actors, glossary integration, standards-based interoperability and automatic layout offer opportunities to study and improve the usefulness of conceptual graphs tools.

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“…FCA techniques and methods, when applied to a formal context allow knowledge representation and handling. With its capacity to extract and represent conceptual structures, FCA has received attention from the SNA (Missaoui et al , 2017; Singh and Kumar, 2014; Poelmans et al , 2011; Snášel et al , 2008, 2009; Freeman, 1996; Freeman and White, 1993; Rome and Haralick, 2005). In our work, we study the problem of analyzing two-mode networks by transforming network data (access log) into a formal context, extracting knowledge, processing premises and conclusions as nodes connected by an edge.…”

Section: Introductionmentioning

confidence: 99%

Identification of substructures in complex networks using formal concept analysis

Neto

Dias²,

Missaoui

et al. 2018

IJWIS

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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.

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Understanding Social Networks Using Formal Concept Analysis

Cited by 21 publications

References 8 publications

Canonical Computational Models Based on Formal Concept Analysis for Social Network Analysis and Representation

Canonical Computational Models Based on Formal Concept Analysis for Social Network Analysis and Representation

Implementation and Visualization of Conceptual Graphs in CharGer

Identification of substructures in complex networks using formal concept analysis

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