LO
Explain why understanding social networks and social capital is important for managers, policy-makers, and society at large
Describe the basics elements and structure of networks
Apply metrics and techniques used in SNA
Visualize and analyse networks, actors and subgroups using SNA software packages
Understand how R can be used for SNACollect social network data
Describe how SNA can be applied in a social media context

Social network analysis(SNA)

Basic network concepts
-Nodes and ties
-Network types : direct or undirect/  one-hop or mutual/ storage: edge lists and matrices
-Tie strength
-Network analysis
-Paths and geodesics


Network characteristics
-Density
-Diameter
-Reciprocity
-Node centrality
-Degree
-Closeness
-Betweenness：The betweenness centrality for each vertex is the number of these shortest paths that pass through the vertex.
-Eigenvector

Making sense of the centrality measures

clustering-homophily

Collecting social network data
-Organizational network analysis (ONA)
-Social media data
-Digital data

Sample size in social network analysis

Visualizing and analysing social networks
-Polinode, NodeXL, and R