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.
À propos de ce cours
Université de Californie à Davis
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
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Meilleurs avis pour ANALYSE DES RÉSEAUX SOCIAUX
This course bringg us with many patience many perspectives and concepts in order to understan social networks. I think it was incredible for my own self-learning, and for my future researches.
This is a great intro to SNA course. In just only 5 weeks, this course will walk you through key concepts, brief logic of SNA, as well as examples from the real world. Highly recommended!
The course was good, but how to collect data for computation to study social networks (other than digital platforms should have been included.
It was really very good learning with coursera especially the mentors for social network analysis were excellent .!!!!!!!
À propos du Spécialisation Sciences sociales computationnelles
For more information please view the Computational Social Science Trailer
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