This course is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. Humans are natural network scientists, as we compute new network configurations all the time, almost unaware, when thinking about friends and family (which are particular forms of social networks), about colleagues and organizational relations (other, overlapping network structures), and about how to navigate delicate or opportunistic network configurations to save guard or advance in our social standing (with society being one big social network itself). While such network structures always existed, computational social science has helped to reveal and to study them more systematically. In the first part of the course we focus on network structure. This looks as static snapshots of networks, which can be intricate and reveal important aspects of social systems. In our hands-on lab, you will also visualize and analyze a network with a software yourself, which will help to appreciate the complexity social networks can take on. During the second part of the course, we will look at how networks evolve in time. We ask how we can predict what kind of network will form and if and how we could influence network dynamics.

Social Network Analysis

Social Network Analysis
This course is part of Computational Social Science Specialization

Instructor: Martin Hilbert
Access provided by Siemens
18,690 already enrolled
242 reviews
What you'll learn
Define networks and discover the languages networks use.
Analyze a social network through data wrangling and visualizing a network.
Discuss what mechanisms generate networks.
Examine social networks analysis using case studies.
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Reviewed on Feb 11, 2022
(1) Interesting, but somewhat eccentric ... I now see why we have taxes ... to subsidize costs of government hubs on networks. (2) See Another use of web-scraping data.
Reviewed on Apr 15, 2020
Excellent course. Learning a lot about social network analysis. Hope to see some advance courses on this domain.
Reviewed on Apr 10, 2020
A great crack course on SNA. It might be a bit difficult for newcomers, but you are making the right choice.
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