Anglų skaidrės. Social Network Analysis (SNA). including a tutorial on concepts and methods. Background Network Analysis. Background Social Science. More examples from social science. Background Other Domains. Practical applications. Why and when to use SNA. Basic Concepts. Representing relations as networks. Entering data on a directed graph. Representing an undirected graph. Ego networks and ‘whole’ networks. Basic Concepts. Adding weights to edges (directed or undirected). Edge weights as relationship strength. Homophily, transitivity, and bridging. Basic Concepts. Note on computational examples. Degree centrality. Paths and shortest paths. Betweenness centrality. Closeness centrality. Eigenvector centrality. Interpretation of measures. Identifying sets of key players. Basic Concepts. Reciprocity (degree of). Density. Clustering. Average and longest distance. Small Worlds. Preferential Attachment. Reasons for preferential attachment. Core-Periphery Structures. Thoughts on Design. Analyzing your own ego-network. Visualizing Facebook ego-network online. Exporting data for offline analysis. Using NodeXL for visualization & analysis. Exporting Facebook ego-network data. More options. Credits and licensing.