Skip to main content
SpringerLink
Log in

Linguistic summarization of fuzzy social and economic networks: an application on the international trade network

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Although plenty of techniques such as link prediction, clustering, and position analysis have been proposed to analyze social and economic networks and patterns of social and economic relationships in various fields, few studies have addressed the transformation of social and economic network data into the knowledge in the form of linguistic summaries. In this study, we propose, for the first time in the literature, iteration, reciprocal and branching-based linguistic summary forms taking into account both the attributes (features) of social and economic actors and the relations between them. We then develop methods for evaluating the degree of truth of the suggested linguistic summary forms by leveraging generalized quantifiers, specifically semi-fuzzy and polyadic quantifiers. The advantages and applicability of the proposed linguistic summary forms are illustrated on the international trade network.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Alexe G, Alexe S, Crama Y, Foldes S, Hammer PL, Simeone B (2004) Consensus algorithms for the generation of all maximal bicliques. Discrete Appl Math 145:11–21

    MathSciNet  MATH  Google Scholar 

  • Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96

    Article  Google Scholar 

  • Bargiela A, Pedrycz W (2003) Granular computing: an introduction. Kluwer Academic Publishers, Dordrecht

    MATH  Google Scholar 

  • Barwise J, Cooper R (1981) Generalized quantifiers and natural language. Linguist Philos 4:159–219

    MATH  Google Scholar 

  • Bastani S, Jafarabad AK, Zarandi MHF (2013) Fuzzy models for link prediction in social networks. Int J Intell Syst 28:768–786

    Google Scholar 

  • Bezdek JC (1981) Pattern recognition with fuzzy objective function algorithms. Kluwer Academic Publishers, Norwell

    MATH  Google Scholar 

  • Bhattacharya K, Mukherjee G, Saramäki J, Kaski K, Manna SS (2008) The international trade network: weighted network analysis and modelling. J Stat Mech Theory Exp 2008:P02002

    MATH  Google Scholar 

  • Boran FE, Akay D (2014) A generic method for the evaluation of interval type-2 fuzzy linguistic summaries. IEEE Trans Cybern 44:1632–1645

    Google Scholar 

  • Boran FE, Akay D, Yager RR (2014) A probabilistic framework for interval type-2 fuzzy linguistic summarization. IEEE Trans Fuzzy Syst 22:1640–1653

    Google Scholar 

  • Boran FE, Akay D, Yager RR (2016) An overview of methods for linguistic summarization with fuzzy sets. Expert Syst Appl 61:356–377

    Google Scholar 

  • Bron C, Kerbosch J (1973) Algorithm 457: finding all cliques of an undirected graph. Commun ACM 16:575–577

    MATH  Google Scholar 

  • Brunelli M, Fedrizzi M, Fedrizzi M (2011) OWA-based fuzzy m-ary adjacency relations in social network analysis. In: Yager RR, Kacprzyk J, Beliakov G (eds) Recent developments in the ordered weighted averaging operators: theory and practice. Springer, Berlin, pp 255–267

    Google Scholar 

  • Brunelli M, Fedrizzi M, Fedrizzi M (2014) Fuzzy m-ary adjacency relations in social network analysis: optimization and consensus evaluation. Inf Fus 17:36–45

    Google Scholar 

  • Casasús-Estellés T, Yager R (2014) Fuzzy concepts in small worlds and the identification of leaders in social networks. In: Laurent A, Strauss O, Bouchon-Meunier B, Yager R (eds) Information processing and management of uncertainty in knowledge-based systems, vol 443. Springer, Montpellier, pp 37–45

    Google Scholar 

  • Chen S-M, Randyanto Y, Cheng S-H (2016) Fuzzy queries processing based on intuitionistic fuzzy social relational networks. Inf Sci 327:110–124

    MathSciNet  MATH  Google Scholar 

  • Chiang D-A, Chow LR, Wang Y-F (2000) Mining time series data by a fuzzy linguistic summary system. Fuzzy Sets Syst 112:419–432

    MATH  Google Scholar 

  • Conde-Clemente P, Alonso JM, Trivino G (2018) Toward automatic generation of linguistic advice for saving energy at home. Soft Comput 22:345–359

    Google Scholar 

  • Delgado M, Sánchez D, Miranda MAV (1999) A survey of methods for evaluating quantified sentences. In: EUSFLAT-ESTYLF joint conference, pp 279–282

  • Delgado M, Sánchez D, Vila MA (2000) Fuzzy cardinality based evaluation of quantified sentences. Int J Approx Reason 23:23–66

    MathSciNet  MATH  Google Scholar 

  • Delgado M, Ruiz MD, Sánchez D, Vila MA (2014) Fuzzy quantification: a state of the art. Fuzzy Sets Syst 242:1–30

    MathSciNet  MATH  Google Scholar 

  • Diaz-Hermida F, Bugarin A (2011) Semi-fuzzy quantifiers as a tool for building linguistic summaries of data patterns. In: IEEE symposium on foundations of computational intelligence (FOCI), pp 45–52

  • Diaz-Hermida F, Losada DE, Bugarin A, Barro S (2005) A probabilistic quantifier fuzzification mechanism: the model and its evaluation for information retrieval. IEEE Trans Fuzzy Syst 13:688–700

    Google Scholar 

  • Diaz-Hermida F, Pereira-Fariña M, Vidal JC, Ramos-Soto A (2017) Characterizing quantifier fuzzification mechanisms: a behavioral guide for applications. Fuzzy Sets Syst 8:8–9

    MATH  Google Scholar 

  • Díaz-Hermida F, Bugarín A, Barro S (2003) Definition and classification of semi-fuzzy quantifiers for the evaluation of fuzzy quantified sentences. Int J Approx Reason 34:49–88

    MathSciNet  MATH  Google Scholar 

  • Díaz-Hermida F, Bugarín A, Cariñena P, Barro S (2004) Voting-model based evaluation of fuzzy quantified sentences: a general framework. Fuzzy Sets Syst 146:97–120

    MathSciNet  MATH  Google Scholar 

  • Dubois D, Prade H (2012) Gradualness, uncertainty and bipolarity: making sense of fuzzy sets. Fuzzy Sets Syst 192:3–24

    MathSciNet  MATH  Google Scholar 

  • Dubois D, Prade H, Sudkamp T (2005) On the representation, measurement, and discovery of fuzzy associations. IEEE Trans Fuzzy Syst 13:250–262

    Google Scholar 

  • Fagiolo G (2010) The international-trade network: gravity equations and topological properties. J Econ Interact Coord 5:1–25

    Google Scholar 

  • Fagiolo G, Reyes J, Schiavo S (2008) On the topological properties of the world trade web: a weighted network analysis. Physica A 387:3868–3873

    MathSciNet  Google Scholar 

  • Fagiolo G, Reyes J, Schiavo S (2009) World-trade web: topological properties, dynamics, and evolution. Phys Rev E 79:036115

    MathSciNet  Google Scholar 

  • Fagiolo G, Reyes J, Schiavo S (2010) The evolution of the world trade web: a weighted-network analysis. J Evolut Econ 20:479–514

    Google Scholar 

  • Fagiolo G, Squartini T, Garlaschelli D (2013) Null models of economic networks: the case of the world trade web. J Econ Interact Coord 8:75–107

    Google Scholar 

  • Gaulier G, Zignago S (2010) Baci: international trade database at the product-level (the 1994–2007 version). Working Paper 2010-23, CEPII, Paris. October 2010

  • Glockner I (2000)Advances in DFS theory. In: TR2000-01, Technische Fakultat, Universitat Bielefeld, Bielefeld, Germany

  • Glöckner I (1997) DFS—an axiomatic approach to fuzzy quantification. In: TR97-06, Techn. Fakultät, Univ. Bielefeld, vol 2, p 10

  • Glöckner I (2004) Evaluation of quantified propositions in generalized models of fuzzy quantification. Int J Approx Reason 37:93–126

    MathSciNet  MATH  Google Scholar 

  • Glöckner I (2009) Generalized fuzzy quantifiers and the modeling of fuzzy branching quantification. Int J Intell Syst 24:624–648

    MATH  Google Scholar 

  • Golbeck J (2013) Analyzing the social web. Morgan Kaufmann, Waltham

    Google Scholar 

  • Hatipoğlu H, Boran FE, Avci M, Akay D (2014) Linguistic summarization of europe brent spot price time series along with the interpretations from the perspective of Turkey. Int J Intell Syst 29:946–970

    Google Scholar 

  • Hausmann R, Hidalgo CA, Bustos S, Coscia M, Chung S, Jimenez J et al (2011) The atlas of economic complexity: mapping paths to prosperity. MIT University Press, Cambridge

    Google Scholar 

  • Havens TC, Bezdek JC, Leckie C, Ramamohanarao K, Palaniswami M (2013) A soft modularity function for detecting fuzzy communities in social networks. IEEE Trans Fuzzy Syst 21:1170–1175

    Google Scholar 

  • Hella L, Väänänen J, Westerståhl D (1997) Definability of polyadic lifts of generalized quantifiers. J Logic Lang Inf 6:305–335

    MathSciNet  MATH  Google Scholar 

  • Hu R-J, Li Q, Zhang G-Y, Ma W-C (2015) Centrality measures in directed fuzzy social networks. Fuzzy Inf Eng 7:115–128

    MathSciNet  Google Scholar 

  • John S (2000) Social network analysis: a handbook, 2nd edn. Sage, London

    Google Scholar 

  • Kacprzyk J, Zadrozny S (2010) Computing with words is an implementable paradigm: fuzzy queries, linguistic data summaries, and natural-language generation. IEEE Trans Fuzzy Syst 18:461–472

    Google Scholar 

  • Kacprzyk J, Zadrożny S (2000) On a fuzzy querying and data mining interface. Kybernetika 36:657–670

    MATH  Google Scholar 

  • Kacprzyk J, Zadrożny S (2016a) Linguistic summarization of the contents of web server logs via the ordered weighted averaging (OWA) operators. Fuzzy Sets Syst 285:182–198

    MathSciNet  Google Scholar 

  • Kacprzyk J, Zadrożny S (2016b) Fuzzy logic-based linguistic summaries of time series: a powerful tool for discovering knowledge on time varying processes and systems under imprecision. Wiley Interdiscip Rev Data Min Knowl Discov 6:37–46

    Google Scholar 

  • Kacprzyk J, Wilbik A, Zadrożny S (2008) Linguistic summarization of time series using a fuzzy quantifier driven aggregation. Fuzzy Sets Syst 159:1485–1499

    MathSciNet  MATH  Google Scholar 

  • Keenan EL, Westerståhl D (1997) Generalized quantifiers in linguistics and logic. In: Benthem JV, Meulen AT (eds) Handbook of logic and language. North-Holland, Amsterdam, pp 837–893

    Google Scholar 

  • Kundu S, Pal SK (2015) FGSN: fuzzy granular social networks—model and applications. Inf Sci 314:100–117

    Google Scholar 

  • Lesot M-J, Moyse G, Bouchon-Meunier B (2016) Interpretability of fuzzy linguistic summaries. Fuzzy Sets Syst 292:307–317

    MathSciNet  MATH  Google Scholar 

  • Li X, Jin YY, Chen G (2003) Complexity and synchronization of the world trade web. Physica A 328:287–296

    MathSciNet  MATH  Google Scholar 

  • Liétard L, Rocacher D (2007) Complex quantified statements evaluated using gradual numbers. In: Castillo O, Melin P, Ross O, Sepúlveda Cruz R, Pedrycz W, Kacprzyk J (eds) Theoretical advances and applications of fuzzy logic and soft computing, vol 42. Springer, Berlin, pp 46–53

    Google Scholar 

  • Liétard L, Rocacher D (2008) Evaluation of quantified statements using gradual numbers. In: José G (ed) Handbook of research on fuzzy information processing in databases. IGI, Hershey, pp 246–269

    Google Scholar 

  • Liu J (2010) Fuzzy modularity and fuzzy community structure in networks. Eur Phys J B 77:547–557

    Google Scholar 

  • Marín N, Sánchez D (2016) On generating linguistic descriptions of time series. Fuzzy Sets Syst 285:6–30

    MathSciNet  Google Scholar 

  • Martin T, Yun S (2009) Fuzzy association rules in soft conceptual hierarchies. In: Fuzzy information processing society, 2009. NAFIPS 2009. Annual meeting of the North American, pp 1–6

  • Martin T, Shen Y, Majidian A (2010) Discovery of time-varying relations using fuzzy formal concept analysis and associations. Int J Intell Syst 25:1217–1248

    MATH  Google Scholar 

  • Niewiadomski A (2007) Interval-valued and interval type-2 fuzzy sets: a subjective comparison. In: 2007 IEEE international fuzzy systems conference, pp 1–6

  • Ramos-Soto A, Bugarín AJ, Barro S, Taboada J (2015) Linguistic descriptions for automatic generation of textual short-term weather forecasts on real prediction data. IEEE Trans Fuzzy Syst 23:44–57

    Google Scholar 

  • Ramos-Soto A, Bugarín A, Barro S (2016a) On the role of linguistic descriptions of data in the building of natural language generation systems. Fuzzy Sets Syst 285:31–51

    MathSciNet  Google Scholar 

  • Ramos-Soto A, Bugarín A, Barro S (2016b) Fuzzy sets across the natural language generation pipeline. Progr Artif Intell 5:261–276

    Google Scholar 

  • Reiter E, Dale R (1997) Building applied natural language generation systems. Nat Lang Eng 3:57–87

    Google Scholar 

  • Rickard JT, Yager RR (2013) Perceptual computing in social networks. In: Presented at the 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), Edmonton, Alberta, Canada

  • Rosenfeld A (1975) Fuzzy graphs. In: Zadeh LA, Fu KS, Shimura M (eds) Fuzzy sets and their applications. Academic Press, New York, pp 77–95

    Google Scholar 

  • Sanchez D, Delgado M, Vila MA, Chamorro-Martinez J (2012) Evaluation of fuzzy quantified sentences: keeping the Boolean properties. In: annual meeting of the North American on fuzzy information processing society (NAFIPS), pp 1–6

  • Sánchez D, Delgado M, Vila MA (2009) Fuzzy quantification using restriction levels. In: Di Gesù V, Pal S, Petrosino A (eds) Fuzzy logic and applications, vol 5571. Springer, Berlin, pp 28–35

    MATH  Google Scholar 

  • Serrano MÁ, Boguñá M (2003) Topology of the world trade web. Phys Rev E 68:015101

    Google Scholar 

  • Serrano MÁ, Boguñá M, Vespignani A (2007) Patterns of dominant flows in the world trade web. J Econ Interact Coord 2:111–124

    Google Scholar 

  • Squartini T, Fagiolo G, Garlaschelli D (2011a) Randomizing world trade. I. A binary network analysis. Phys Rev E 84:046117

    Google Scholar 

  • Squartini T, Fagiolo G, Garlaschelli D (2011b) Randomizing world trade. II. A weighted network analysis. Phys Rev E 84:046118

    Google Scholar 

  • Stakias G, Psoras M, Glykas M (2013) Fuzzy cognitive maps in social and business network analysis. In: Glykas M (ed) Business process management: theory and applications. Springer, Berlin, pp 241–279

    Google Scholar 

  • Su J, Havens TC (2014) A generalized fuzzy T-norm formulation of fuzzy modularity for community detection in social networks. In: Jamshidi M, Kreinovich V, Kacprzyk J (eds) Advance trends in soft computing: proceedings of WCSC 2013, December 16–18, San Antonio, Texas, USA. Springer, Cham, pp 65–76

  • Szymanik J (2010) Computational complexity of polyadic lifts of generalized quantifiers in natural language. Linguist Philos 33:215–250

    Google Scholar 

  • Tarjan R (1972) Depth-first search and linear graph algorithms. SIAM J Comput 1:146–160

    MathSciNet  MATH  Google Scholar 

  • The World Bank, Economy & Growth Indicators. Available: http://www.worldbank.org/

  • The Observatory of Economic Complexity, Economic Complexity Index. Available: http://atlas.media.mit.edu

  • Trivino G, Sugeno M (2013) Towards linguistic descriptions of phenomena. Int J Approx Reason 54:22–34

    Google Scholar 

  • Tzekina I, Danthi K, Rockmore DN (2008) Evolution of community structure in the world trade web. Eur Phys J B Condens Matter Complex Syst 63:541–545

    MATH  Google Scholar 

  • Van Benthem J (1983) Determiners and logic. Linguist Philos 6:447–478

    MATH  Google Scholar 

  • Wasserman S, Faust K (1994) Social network analysis : methods and applications. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Wi H, Jung M (2014) An evaluation fuzzy model and its application for knowledge-based social network. In: Pedrycz W, Chen SM (eds) Social networks: a framework of computational intelligence. Springer, Cham, pp 313–332

    Google Scholar 

  • Wu D, Mendel JM (2011) Linguistic summarization using IF-THEN rules and interval type-2 fuzzy sets. IEEE Trans Fuzzy Syst 19:136–151

    Google Scholar 

  • Yager RR (1982) A new approach to the summarization of data. Inf Sci 28:69–86

    MathSciNet  MATH  Google Scholar 

  • Yager RR (1996) Quantifier guided aggregation using OWA operators. Int J Intell Syst 11:49–73

    Google Scholar 

  • Yager RR (2008) Intelligent social network analysis using granular computing. Int J Intell Syst 23:1197–1219

    MATH  Google Scholar 

  • Yager RR (2010) Concept representation and database structures in fuzzy social relational networks. IEEE Trans Syst Man Cybern Part A Syst Hum 40:413–419

    Google Scholar 

  • Yager RR, Reformat MZ (2013) Looking for like-minded individuals in social networks using tagging and E fuzzy sets. IEEE Trans Fuzzy Syst 21:672–687

    Google Scholar 

  • Yager RR, Yager RL (2013) Social networks: querying and sharing mined information. In: 46th Hawaii international conference on system sciences (HICSS), pp 1435–1442

  • Zadeh LA (1983) A computational approach to fuzzy quantifiers in natural languages. Comput Math Appl 9:149–184

    MathSciNet  MATH  Google Scholar 

  • Zadeh LA (1996) Fuzzy logic = computing with words. IEEE Trans Fuzzy Syst 4:103–111

    Google Scholar 

  • Zadeh LA (1999) From computing with numbers to computing with words. From manipulation of measurements to manipulation of perceptions. IEEE Trans Circuits Syst I Fund Theory Appl 46:105–119

    MathSciNet  MATH  Google Scholar 

  • Zadeh LA, Abbasov AM, Shahbazova SN (2015) Fuzzy-based techniques in human-like processing of social network data. Int J Uncertain Fuzziness Knowl Based Syst 23:1–14

    Google Scholar 

  • Zadrożny S, De Tré G, De Caluwe R, Kacprzyk J (2009) An overview of fuzzy approaches to flexible database querying. In: Erickson J (ed) Database technologies: concepts, methodologies, tools, and applications, vol 4. IGI Global, Barcelona, pp 135–156

    Google Scholar 

  • Zhang S, Wang R-S, Zhang X-S (2007) Identification of overlapping community structure in complex networks using fuzzy-means clustering. Physica A 374:483–490

    Google Scholar 

Download references

Acknowledgements

Serkan GENÇ was supported by The Scientific and Technological Research Council of Turkey (TÜBITAK) –BIDEB National Doctoral Fellowship Program.

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Gazi University, 06570, Ankara, Turkey

    Serkan Genç & Diyar Akay

  2. Department of Energy Systems Engineering, Faculty of Technology, Gazi University, 06500, Ankara, Turkey

    Fatih Emre Boran

  3. Machine Intelligence Institute, Iona College, New Rochelle, NY, 10805, USA

    Ronald R. Yager

Authors
  1. Serkan Genç
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diyar Akay
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fatih Emre Boran
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ronald R. Yager
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Serkan Genç.

Ethics declarations

Conflict of interest

Authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Additional information

Communicated by V. Loia.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Genç, S., Akay, D., Boran, F.E. et al. Linguistic summarization of fuzzy social and economic networks: an application on the international trade network. Soft Comput 24, 1511–1527 (2020). https://doi.org/10.1007/s00500-019-03982-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-019-03982-9

Keywords

Search

Navigation