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>> YOUR LINK HERE: ___ http://youtube.com/watch?v=PT99WF1VEws

Basics of Social Network Analysis • In this video Dr Nigel Williams explores the basics of Social Network Analysis (SNA): Why and how SNA can be used in Events Management Research. • The freeware sound tune 'MFF - Intro - 160bpm' by Kenny Phoenix http://www.last.fm/music/Kenny+Phoenix was downloaded from Flash Kit • http://www.flashkit.com/loops/Techno-... • The video's content includes: • Why Social Network Analysis (SNA)? • Enables us to segment data based on user behavior. • Understand natural groups that have formed: • a. topics • b. personal characteristics • Understand who are the important people in these groups. • • Analysing Social Networks: • Data Collection Methods: • a. Surveys • b. Interviews • c. Observations • Analysis: • a. Computational analysis of matrices • Relationships: • A. is connected to B. • SNA Introduction: • [from] A. Directed Graph [to] B. e.g. Twitter replies and mentions • A. Undirected Graph B. e.g. family relationships • What is Social Network Analysis? • Research technique that analyses the Social structure that emerges from the combination of relationships among members of a given population (Hampton Wellman (1999); Paolillo (2001); Wellman (2001)). • Social Network Analysis Basics: Node and Edge • Node: • “actor” or people on which relationships act • Edge: • relationship connecting nodes; can be directional • Social Network Analysis Basics: Cohesive Sub-group • Cohesive Sub-group: • a. well-connected group, clique, or cluster, e.g. A, B, D, and E • Social Network Analysis Basics: Key Metrics • Centrality (group or individual measure): • a. Number of direct connections that individuals have with others in the group (usually look at incoming connections only). • b. Measure at the individual node or group level. • Cohesion (group measure): • a. Ease with which a network can connect. • b. Aggregate measure of shortest path between each node pair at network level reflects average distance. • Density (group measure): • a. Robustness of the network. • b. Number of connections that exist in the group out of 100% possible. • Betweenness (individual measure): • a. Shortest paths between each node pair that a node is on. • b. Measure at the individual node level. • Social Network Analysis Basics: Node Roles: • Node Roles: • Peripheral – below average centrality, e.g. C. • Central connector – above average centrality, e.g. D. • Broker – above average betweenness, e.g. E. • References and Reading • Hampton, K. N., and Wellman, B. (1999). Netville Online and Offline Observing and Surveying a Wired Suburb. American Behavioral Scientist, 43(3), pp. 475-492. • Smith, M. A. (2014, May). Identifying and shifting social media network patterns with NodeXL. In Collaboration Technologies and Systems (CTS), 2014 International Conference on IEEE, pp. 3-8. • Smith, M., Rainie, L., Shneiderman, B., and Himelboim, I. (2014). Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. Pew Research Internet Project.

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