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Agent-Based Simulation of Cultural Events Impact on Social Capital Dynamics

  • Darius PlikynasEmail author
  • Rimvydas LaužikasEmail author
  • Leonidas SakalauskasEmail author
  • Arūnas MiliauskasEmail author
  • Vytautas DulskisEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1037)

Abstract

Modern societies are very rapidly changing in the context of complex and dynamic technological, economic and cultural environments. Admittedly, the latter environment is very vague and much less understood in terms of formal modelling of underlying processes. Evidently, in the era of globalization and radicalization, there is an urgent need to have some applicable models to simulate and foresee how particular cultural activities form social cohesion, dispersion, clusterization or radicalization in social groups or society in general. In this regard, presented multidisciplinary research paper is focused on modelling and simulation of stylized cultural events impact to social capital dynamics and distribution. Presented agent-based simulation approach rests upon conceptual model, which employs CIDOC-CRM methodology. OECD scheme is used to estimate social capital metrics - personal relationships, social network support, civic engagement, trust and cooperative norms. Agent-based simulation model is described using ODD standardized protocol. NetLogo MAS platform is used as a simulation environment. Obtained simulation results start from a well-known Axelrod agent-based physical neighbourhood interaction model, which we, following modern empirical observations, expanded for (i) the long-range interaction approach (broadcasted cultural events) and (ii) neighbourhood interaction in the social capital dimensions. Simulation results reveal some basic conditions under which cohesion, clustering or radicalization behavioural patterns can emerge in the simulated society.

Keywords

Agent-based simulation ODD protocol CIDOC-CRM Social capital Cultural events 

Notes

Acknowledgment

This research was funded by a grant (No. P-MIP-17-368) from the Research Council of Lithuania.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Data Science and Digital TechnologiesVilnius UniversityVilniusLithuania

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