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Information Diffusion as a Mechanism for Natural Evolution of Social Networks

  • Kyle BahrEmail author
  • Masami Nakagawa
Chapter
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

The social license to operate is an emergent convergence of opinion, the production and durability of which is highly interdependent with the structure of the stakeholder network. This structure evolves over time as new links are formed and old links decay. In this paper, we propose a social license model in which agent interactions lead to the evolution of network structures, which are then classified according to observed stakeholder networks.

Keywords

Agent-based modeling Social network generation Opinion diffusion Social license to operate Network evolution 

References

  1. Adler, P. S., & Kwon, S.-W. (2002). Social capital: Prospects for a new concept. The Academy of Management Review, 27(1), 17–40.CrossRefGoogle Scholar
  2. Albert, R., & Barabási, A.-L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 48–94.ADSMathSciNetCrossRefGoogle Scholar
  3. Axelrod, R. (1997). The dissemination of culture. Journal of Conflict Resolution, 41(2), 203–226.CrossRefGoogle Scholar
  4. Bahr, K., & Nakagawa, M. (2017). The effect of bidirectional opinion diffusion on social license to operate. Environment, Development and Sustainability, 19(4), 1235–1245.CrossRefGoogle Scholar
  5. Barabási, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.ADSMathSciNetCrossRefGoogle Scholar
  6. Borgatti, S. P. (2005). Centrality and network flow. Social Networks, 27(1), 55–71.ADSMathSciNetCrossRefGoogle Scholar
  7. Boutilier, R. (2009). Stakeholder politics social capital, sustainable development, and the corporation. Stanford: Stanford University Press.Google Scholar
  8. Boutilier, R., & Thomson, I. (2009). How to measure the socio-political risk in a project. In XXVIII Convención Minera Internacional, pp. 438–444.Google Scholar
  9. Deffuant, G., Neau, D., Amblard, F., & Weisbuch, G. (2000). Mixing beliefs among interacting agents. Advances in Complex Systems, 3(01n04), 87–98.CrossRefGoogle Scholar
  10. Erdös, P., & Rényi, A. (1959). On random graphs. Publicationes Mathematicae, 6, 290–297.MathSciNetzbMATHGoogle Scholar
  11. Freeman, R. E., & Mc Vea, J. (1984). A stakeholder approach to strategic management. (Working Paper 01-02). Charlottesvill: Darden Graduate School of Business Administration.Google Scholar
  12. Gilbert, N. (2008). Agent-based models. Thousand Oaks: Sage Publications Inc.CrossRefGoogle Scholar
  13. Hegselmann, R., & Krause, U. (2002). Opinion dynamics and bounded confidence: Models, analysis and simulation. Journal of Artificial Societies and Social Simulation, 5(3), 1–33.Google Scholar
  14. Judd, J. S., & Kearns, M. (2008). Behavioral experiments in networked trade. In Proceedings 9th ACM Conference on Electronic Commerce – EC ’08, p. 150.Google Scholar
  15. Kearns, M. (2012). Experiments in social computation. Communications of the ACM, 55(10), 56.CrossRefGoogle Scholar
  16. Mitchell, R. K., Agle, B. R., & Wood, D. J. (1997). Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts. Academy of Management Review, 22(4), 853–886.CrossRefGoogle Scholar
  17. Nakagawa, M., Bahr, K., & Levy, D. (2012). Scientific understanding of stakeholders’ behavior in mining community. Environment, Development and Sustainability, 15(2), 497–510.CrossRefGoogle Scholar
  18. Okada, I. (2011). An agent-based model of sustainable corporate social responsibility activities. Journal of Artificial Societies and Social Simulation, 14(3), 1–29.MathSciNetCrossRefGoogle Scholar
  19. Parsons, R., & Moffat, K. (2014). Constructing the meaning of social licence. Social Epistemology, 28(3–4), 340–363.CrossRefGoogle Scholar
  20. Preusse, J., Kunegis, J., Thimm, M., & Sizov, S. (2014). DecLiNe – Models for decay of links in networks. arXiv.org. https://dblp.org/rec/bib/journals/corr/PreusseKTS14; http://arxiv.org/abs/1403.4415
  21. Prno, J., & Slocombe, D. (2012). Exploring the origins of ‘social license to operate’ in the mining sector: Perspectives from governance and sustainability theories. Resources Policy, 37(3), 346–357.CrossRefGoogle Scholar
  22. Roberts, S. B. G., & Dunbar, R. I. M. (2015). Managing relationship decay: Network, gender, and contextual effects. Human Nature, 26(4), 426–450.CrossRefGoogle Scholar
  23. Thomson, I., & Boutilier, R. G. (2011). Social license to operate. In P. Darling (Ed.), SME mining engineering handbook (3rd ed., pp. 1779–1796). Englewood: Society for Mining, Metallurgy, and Exploration, Inc.Google Scholar
  24. Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.ADSCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Tohoku UniversitySendaiJapan
  2. 2.Colorado School of MinesGoldenUSA

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