Computational Social Science Methods Coursera

Overview

The results are all around us, every day, reaching from the services provided by the world’s most valuable companies, over the hidden influence of governmental agencies, to the power of social and political movements. All of them study human behavior in order to shape it. In short, all of them do social science by computational means.

In this Computational Social Science Methods course offered by Coursera in partnership with UC Davis we answer three questions: I. Why Computational Social Science (CSS) now? II. What does CSS cover? III. What are examples of CSS?

In this last part, we take a bird’s-eye view on four main applications of CSS. First, Prof. Blumenstock from UC Berkeley discusses how we can gain insights by studying the massive digital footprint left behind today’s social interactions, especially to foster international development. Second, Prof. Shelton from UC Riverside introduces us to the world of machine learning, including the basic concepts behind this current driver of much of today's computational landscape. Prof. Fowler, from UC San Diego introduces us to the power of social networks, and finally, Prof. Smaldino, from UC Merced, explains how computer simulation help us to untangle some of the mysteries of social emergence.

What you'll learn

• Examine the history and current challenges faced by Social Science through the digital revolution.

• Configure a machine to create a database that can be used for analysis.

• Discuss what is artificial intelligence (AI) and train a machine.

• Discover how social networks and human dynamics create social systems and recognizable patterns.