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Social Network Analysis

Social Network Analysis

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9.9/10 (Our Score)
Product is rated as #2 in category Data Science

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.

Instructor Details

Martin Hilbert pursues a multidisciplinary approach to understanding the role of information and knowledge in the development of complex social systems. Before joining UC Davis, Prof. Hilbert created and led the Information Society Program of the United Nations Secretariat for Latin America and the Caribbean. This program aims at fostering the impact of digital technologies. In his 15 years as United Nations Economic Affairs Officer he has provided hands-on technical assistance in the field of digital development to Presidents, government experts, legislators, diplomats, NGOs, and companies in over 20 countries. Policy makers from the highest political levels have officially recognized the impact of his projects. He retired early from his life-long appointment with the UN, because he wanted to be an active part of the exciting process of making use of these same digital technologies to better understand society. He joined the University of California in 2014 to be able to dedicate more time and energy to "Computational Social Science". He regularly still does consulting work for the UN and other private and public clients, applying new CSS methods in practice. He has written five books about digital technology for international development and has published in academic journals in the fields of communication, economic development, information science, psychology, ecology and evolution, political science, complex systems, women’s studies, and forecasting. His findings have been featured in popular outlets. Like Scientific American, PBS, Discovery, NatGeo, Wall Street Journal, Washington Post, The Economist, NPR, BBC, Die Welt, Correio Braziliense, ElMundo, among others. International perspectives are no mere theory for Prof. Hilbert, as he speaks five languages and has traveled to over 70 countries.

Specification: Social Network Analysis

Duration 18 hours
Year 2020
Level Beginner
Certificate Yes
Quizzes Yes

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    Domieck

    Learned a lot more than expected and Hilbert is a great professor

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