Formal Concept Analysis Applied to Professional Social Networks Analysis

Paula R. C. Silva, Sérgio M. Dias, Wladmir C. Brandão, Mark A. Song, Luis E. Zárate

2017

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.

References

  1. Ali, S. S., Bentayeb, F., Missaoui, R., and Boussaid, O. (2014). An Efficient Method for Community Detection Based on Formal Concept Analysis, pages 61-72. Springer International Publishing, Cham.
  2. Atzmueller, M. (2015). Subgroup and community analytics on attributed graphs. In Proceedings of the Workshop on Social Network Analysis using Formal Concept Analysis.
  3. Aufaure, M.-A. and Le Grand, B. (2013). Advances in fcabased applications for social networks analysis. Int. J. Concept. Struct. Smart Appl., 1(1):73-89.
  4. Banerjee, S., Badr, Y., and Al-shammari, E. T. (2014). Social Networks: A Framework of Computational Intelligence, volume 526. Springer Berlin Heidelberg.
  5. Barysheva, A., Golubtsova, A., and Yavorskiy, R. (2015). Profiling less active users in online communities. In Proceedings of the Workshop on Social Network Analysis using Formal Concept Analysis.
  6. Bertet, K. and Monjardet, B. (2010). The multiple facets of the canonical direct unit implicational basis. Theoretical Computer Science, 411(22-24):2155 - 2166.
  7. Branda˜o, H. P. and Guimara˜es, T. d. A. (2001). Gesta˜o de competeˆncias e gesta˜o de desempenho: tecnologias distintas ou instrumentos de um mesmo construto? Revista de Administrac¸a˜o de empresas, 41(1):8-15.
  8. Cast, C. (2016). Jobs rated report 2016: Ranking 200 jobs. Accessed in 2016-12-12.
  9. Codocedo, V., Baixeries, J., Kaytoue, M., and Napoli, A. (2016). Contributions to the formalization of orderlike dependencies using fca. In Proceedings of the 5th International Workshop What can FCA do for Artificial Intelligence. CEUR-WS.
  10. Cordero, P., Enciso, M., Mora, A., Ojeda-Aciego, M., and Rossi, C. (2015). Knowledge discovery in social networks by using a logic-based treatment of implications. Know.-Based Syst., 87(C):16-25.
  11. Cuvelier, E. and Aufaure, M.-A. (2011). A buzz and ereputation monitoring tool for twitter based on galois lattices. In Conceptual Structures for Discovering Knowledge, pages 91-103. Springer, Berlin Heidelberg.
  12. Dias, S. M. (2016). Reduc¸ a˜o de Reticulados Conceituais (Concept Lattice Reduction). PhD thesis, Department of Computer Science of Federal University of Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil. In Portuguese.
  13. Durand, T. (1998). Forms of incompetence. In Proceedings Fourth International Conference on CompetenceBased Management. Oslo: Norwegian School of Management.
  14. Ganter, B., Stumme, G., and Wille, R. (2005). Formal concept analysis: foundations and applications, volume 3626. Springer Science & Business Media.
  15. Ganter, B. and Wille, R. (2012). Formal concept analysis: mathematical foundations. Springer Science & Business Media.
  16. Jota Resende, G., De Moraes, N. R., Dias, S. M., Marques Neto, H. T., and Zarate, L. E. (2015). Canonical computational models based on formal concept analysis for social network analysis and representation. In Web Services (ICWS), 2015 IEEE International Conference on, pages 717-720. IEEE.
  17. Kontopoulos, E., Berberidis, C., Dergiades, T., and Bassiliades, N. (2013). Ontology-based sentiment analysis of twitter posts. Expert Systems with Applications, 40(10):4065 - 4074.
  18. Krajc?i, S. (2014). Social Network and Formal Concept Analysis, pages 41-61. Springer International Publishing, Cham.
  19. Li, L., Zheng, G., Peltsverger, S., and Zhang, C. (2016). Career trajectory analysis of information technology alumni: A linkedin perspective. In Proceedings of the 17th Annual Conference on Information Technology Education, SIGITE 7816, pages 2-6, New York, NY, USA. ACM.
  20. LinkedIn (2016). About linkedin. Accessed in 2016-12-02.
  21. Lorenzo, E. R., Cordero, P., Enciso, M., Missaoui, R., and Mora, A. (2016). Caisl: Simplification logic for conditional attribute implications. In CLA.
  22. Neto, S. M., Song, M., Dias, S., et al. (2015a). Minimal cover of implication rules to represent two mode networks. In 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), volume 1, pages 211- 218. IEEE.
  23. Neto, S. M., Song, M. A., Dias, S. M., and Zárate, L. E. (2015b). Using implications from fca to represent a two mode network data. nternational Journal of Software Engineering and Knowledge Engineering (IJSEKE).
  24. Neznanov, A. and Parinov, A. (2015). Analyzing social networks services using formal concept analysis research toolbox. In Proceedings of the Workshop on Social Network Analysis using Formal Concept Analysis.
  25. Rome, J. E. and Haralick, R. M. (2005). Towards a Formal Concept Analysis Approach to Exploring Communities on the World Wide Web, pages 33-48. Springer Berlin Heidelberg, Berlin, Heidelberg.
  26. Russell, M. A. (2013). Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More. ” O'Reilly Media, Inc.”.
  27. Snasel, V., Horak, Z., Kocibova, J., and Abraham, A. (2009). Analyzing social networks using fca: Complexity aspects. In Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT 7809. IEEE/WIC/ACM International Joint Conferences on, volume 3, pages 38-41.
  28. Soldano, H., Santini, G., and Bouthinon, D. (2015). Abstract and local concepts in attributed networks. In Proceedings of the Workshop on Social Network Analysis using Formal Concept Analysis.
  29. Stattner, E. and Collard, M. (2012). Social-based conceptual links: Conceptual analysis applied to social networks. In Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on, pages 25-29.
  30. Taouil, R. and Bastide, Y. (2001). Computing Proper Implications. In Proceedings of the International Conference on Conceptual Structures - ICCS, pages 46-61, Stanford, CA US.
  31. Xu, Y., Li, Z., Gupta, A., Bugdayci, A., and Bhasin, A. (2014a). Modeling professional similarity by mining professional career trajectories. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1945- 1954. ACM.
  32. Xu, Y., Li, Z., Gupta, A., Bugdayci, A., and Bhasin, A. (2014b). Modeling professional similarity by mining professional career trajectories. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1945- 1954. ACM.
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Paper Citation


in Harvard Style

Silva P., Dias S., Brandão W., Song M. and Zárate L. (2017). Formal Concept Analysis Applied to Professional Social Networks Analysis . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 123-134. DOI: 10.5220/0006333401230134


in Bibtex Style

@conference{iceis17,
author={Paula R. C. Silva and Sérgio M. Dias and Wladmir C. Brandão and Mark A. Song and Luis E. Zárate},
title={Formal Concept Analysis Applied to Professional Social Networks Analysis},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={123-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006333401230134},
isbn={978-989-758-247-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Formal Concept Analysis Applied to Professional Social Networks Analysis
SN - 978-989-758-247-9
AU - Silva P.
AU - Dias S.
AU - Brandão W.
AU - Song M.
AU - Zárate L.
PY - 2017
SP - 123
EP - 134
DO - 10.5220/0006333401230134