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Social Networks: Agent-based Modelling and Social Network Analysis with PAJEK Richard Taylor¹ and Gindo Tampubolon² ¹Centre for Policy Modelling, Manchester Metropolitan University ²Centre for Research on Innovation and Competition, University of Manchester ESRC Research Methods Festival, Oxford, 17th-20th July 2006, & Oxford Spring School, Dept. of Politics and International Relations Outline of Tutorial Morning Afternoon • Graph theory and Social Networks • Social Network Analysis measures and techniques • Agent-based Modelling • PAJEK Software • 2 Demo Models • ABM Methodology JinGirNew friendship Innovation Model • Software utilities JAVA REPAST REALJ Concluding session: • Discussion on issues for combining the 2 methods Methodological Overview • Quantitative and numerical • Formal language • Indices / metrics • Visualisation • A range of phenomena (e.g…) SNA Background • Social interactions are structured; structure (i.e. the social climate) determines the nature of the parts • the perceptions, behaviour, and the limitations and opportunities for action • Concern for structure of informal relations/groupings as opposed to formal roles (i.e. micro-foundational) • Relations which the individuals themselves recognise • Mechanisms by which social aggregates are sustained and transformed over time • To identify leaders, isolated individuals, sub-groups etc. Findings • Systematic interdependence between the attitudes held by different individuals within a group (Scott, 1991) • Leading to cohesion, social pressure, cooperation, solidarity • Existence of ‘cliques’ “placing people in society” • Role played by conflict and power Combination of graph theory and sociological framework Suggests SNA meets “a need for appropriate concepts to use in understanding complex societies” Graph Theory and SNA Graph / network theory A graph G(V,E) consists of a set of vertices V representing individuals or objects and a set of edges E representing relationships between the individuals or objects • • • • • Directed and undirected graphs, valued graphs Degree, indegree, outdegree Density, connectedness, subgraphs Average path length, cliquishness, clustering Centrality, periphery More basic concepts from Analytic Technologies
