Minimal implications base for social network analysis

Purpose
Currently, social network (SN) analysis is focused on the discovery of activity and social relationship patterns. Usually, these relationships are not easily and completely observed. Therefore, it is relevant to discover substructures and potential behavior patterns in SN. Recently, formal concept analysis (FCA) has been applied for this purpose. FCA is a concept analysis theory that identifies concept structures within a data set. The representation of SN patterns through implication rules based on FCA enables the identification of relevant substructures that cannot be easily identified. The authors’ approach considers a minimum and irreducible set of implication rules (stem base) to represent the complete set of data (activity in the network). Applying this to an SN is of interest because it can represent all the relationships using a reduced form. So, the purpose of this paper is to represent social networks through the steam base.

Design/methodology/approach
The authors’ approach permits to analyze two-mode networks by transforming access activities of SN into a formal context. From this context, it can be extracted to a minimal set of implications applying the NextClosure algorithm, which is based on the closed sets theory that provides to extract a complete, minimal and non-redundant set of implications. Based on the minimal set, the authors analyzed the relationships between premises and their respective conclusions to find basic user behaviors.

Findings
The experiments pointed out that implications, represented as a complex network, enable the identification and visualization of minimal substructures, which could not be found in two-mode network representation. The results also indicated that relations among premises and conclusions represent navigation behavior of SN functionalities. This approach enables to analyze the following behaviors: conservative, transitive, main functionalities and access time. The results also demonstrated that the relations between premises and conclusions represented the navigation behavior based on the functionalities of SN. The authors applied their approach for an SN for a relationship to explore the minimal access patterns of navigation.

Originality/value
The authors present an FCA-based approach to obtain the minimal set of implications capable of representing the minimum structure of the users’ behavior in an SN. The paper defines and analyzes three types of rules that form the sets of implications. These types of rules define substructures of the network, the capacity of generation users’ behaviors, transitive behavior and conservative capacity when the temporal aspect is considered.

 

Paula Raissa, Sérgio Dias, Mark Song, Luis Zárate, (2018) “Minimal implications base for social network analysis”, International Journal of Web Information Systems, Vol. 14 Issue: 1, pp.62-77, https://doi.org/10.1108/IJWIS-04-2017-0028

Identification of substructures in complex networks using formal concept analysis

Sebastião M. Neto, Sérgio Dias, Rokia Missaoui, Luis Zárate, Mark Song, (2018) “Identification of substructures in complex networks using formal concept analysis”, International Journal of Web Information Systems, Vol. 14 Issue: 3, pp.281-298, https://doi.org/10.1108/IJWIS-10-2017-0067

Professional Competence Identification Through Formal Concept Analysis

Abstract

As the job market has become increasingly competitive, people who are looking for a job placement have needed help to increase their competence to achieve a job position. The competence is defined by the set of skills that is necessary to execute an organizational function. In this case, it would be helpful to identify the sets of skills which is necessary to reach job positions. Currently, the on-line professional social networks are attracting the interest from people all around the world, whose their goals are oriented to business relationships. Through the available amount of information in this kind of networks it is possible to apply techniques to identify the competencies that people have developed in their career. In this scenario it has been fundamental the adoption of computational methods to solve this problem. The formal concept analysis (FCA) has been a effective technique for data analysis area, because it allows to identify conceptual structures in data sets, through conceptual lattice and implications. A specific set of implications, know as proper implications, represent the set of conditions to reach a specific goal. So, in this work, we proposed a FCA-based approach to identify and analyze the professional competence through proper implications.

Keywords

Formal concept analysis Proper implications Professional competence On-line social networks 

Silva P.R., Dias S.M., Brandão W.C., Song M.A., Zárate L.E. (2018) Professional Competence Identification Through Formal Concept Analysis. In: Hammoudi S., Śmiałek M., Camp O., Filipe J. (eds) Enterprise Information Systems. ICEIS 2017. Lecture Notes in Business Information Processing, vol 321. Springer, Cham
https://doi.org/10.1007/978-3-319-93375-7_3

Journal of Big Data

Aims and scope

The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.

Formal Concept Analysis Applied to Professional Social Networks Analysis

Best Student Paper Award in area of Databases and Information Systems Integration for the paper entitled: Formal Concept Analysis applied to Professional Social Networks Analysis, 19th International Conference on Enterprise Information Systems (ICEIS). http://www.iceis.org/PreviousAwards.aspx?y=2018

Abstract: From the recent proliferation of online social networks, a set of specific type of social network is attracting more and more interest from people all around the world. It is professional social networks, where the users’ interest is oriented to business. The behavior analysis of this type of user can generate knowledge about competences that people have been developed in their professional career. In this scenario, and considering the available amount of information in professional social networks, it has been fundamental the adoption of effective computational methods to analyze these networks. The formal concept analysis (FCA) has been a effective technique to social network analysis (SNA), because it allows identify conceptual structures in data sets, through conceptual lattice and implication rules. Particularly, a specific set of implications rules, know as proper implications, can represent the minimum set of conditions to reach a specific goal. In this work, we proposed a FCA-based approach to identify relations among professional competences through proper implications. The experimental results, with professional profiles from LinkedIn and proper implications   extracted from PropIm algorithm, shows the minimum sets of skills that is necessary to reach job positions.

Silva, P., Dias, S., Brandão, W., Song, M. and Zárate, L. Formal Concept Analysis Applied to Professional Social Networks Analysis. In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) – Volume 1, pages 123-134. ISBN: 978-989-758-247-9 Copyright © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.