This is an audio version of the Wikipedia Article:
Social network analysis


00:01:15 1 History
00:02:47 2 Metrics
00:02:56 2.1 Connections
00:04:05 2.2 Distributions
00:05:41 2.3 Segmentation
00:06:24 3 Modelling and visualization of networks
00:09:10 3.1 Social networking potential
00:11:08 4 Practical applications
00:12:10 4.1 Security applications
00:13:24 4.2 Textual analysis applications
00:14:18 4.3 Internet applications
00:14:53 4.3.1 Social Media Internet Applications
00:15:16 4.4 In computer-supported collaborative learning
00:16:20 4.4.1 Key terms
00:18:11 4.4.2 Unique capabilities
00:19:20 4.4.3 Other methods used alongside SNA



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"The only true wisdom is in knowing you know nothing."
- Socrates



SUMMARY
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Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, memes spread, information circulation, friendship and acquaintance networks, business networks, social networks, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through sociograms in which nodes are represented as points and ties are represented as lines.
Social network analysis has emerged as a key technique in modern sociology. It has also gained a significant following in anthropology, biology, demography, communication studies, economics, geography, history, information science, organizational studies, political science, social psychology, development studies, sociolinguistics, and computer science and is now commonly available as a consumer tool (see the list of SNA software).