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Lecture 9

Lecture 9. Introduction to Social Networks: Networks Structures and Information Systems. What is Social Network Analysis?. Network analysis is the study of social relations among a set of actors. It is a field of study, not just a method.

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Lecture 9

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  1. Lecture 9 Introduction to Social Networks: Networks Structures and Information Systems

  2. What is Social Network Analysis? • Network analysis is the study of social relations among a set of actors. It is a field of study, not just a method. • “Social network analysis involves theorizing, model building and empirical research focused on uncovering the patterning of links among actors. It is concerned also with uncovering the antecedents and consequences of recurrent patterns.” (Linton Freeman)

  3. The network perspective People (nodes) Ties (edges)

  4. Ties in a social network • Directed or undirected • Simplex or multiplex • Valued or unvalued 7

  5. What is a Social Network? • A set of dyadic ties, all of the same type, among a set of actors • Actors can be persons, organizations, groups • A tie is an instance of a specific social relationship

  6. Network Relations • Among Individuals • Kinship • Role-based (friend of) • Cognitive/Perceptual (knows, aware of) • Affiliations • Affective (likes, trusts) • Communication • Among Organizations • Buy from / Sell to • Owns shares of • Joint ventures

  7. Key Perspectives in Social Network Analysis • Focus on relationships between actors rather than just the attributes of actors. • Interdependent viewrather than atomistic (individualist) view of social processes and effects. • Social structureaffects substantive outcomes (which is a philosophical departure from other traditions)

  8. Interdisciplinary Field of Study • Computer Science • Designing and understanding complex network structures • Mathematics, Physics • Methods, complex systems analysis • Social Science (Sociology, Social Psychology, Economics) • Theories and measurement of social networks, using networks to understand human behavior

  9. Multiple Levels of Analysis • Individual Level • How does individual position in a network affect various outcomes for the individual? • Systems Level • How does the network structure as a whole affect outcomes for various tasks?

  10. Network Data Collection • Common Types: • Survey • Interviews • Affiliation/membership records • Behavioral (e.g., observation of communication patterns) • Experiments Data obtained through manyeyes and graphed: http://www.esv.org/blog/2007/01/mapping.nt.social.networks

  11. Types of Network Data • One mode Two mode • Whole network Egocentric A B A B C School A

  12. Non-directed versus Directed Graphs A B A B C C

  13. Analyzing Social Networks A B D C Simple Adjacency Matrix

  14. Some Key Principles in Social Networks • Degree • Density • Centrality

  15. Degree in Social Networks

  16. Density in Social Networks Low Density High Density / Integrated “Radial” (Valente)

  17. Centrality in Social Networks • Degree Centrality • Closeness Centrality • Betweeness Centrality

  18. Why all of this sudden interest? • The strength of the “Strength of Weak Ties” argument. • Granovetter (1973) • Argues that ‘weaker’ peripheral ties build heterogeneous networks, which in turn provide access to new and useful information. • Heterogeneity through weak-ties widely accepted as a “good thing” for communication • Access to jobs • Access to other opportunities • Helps distribute ideas, innovations

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