Date: May 12, 2014 - May 18, 2014
Bio: This course caught my curiosity as it was only a week long, so I was expecting a sort of cram school / high intensity course load over a week. This was not the case.
The topic of Big Data and Social Physics is, in this context, a specific focus within behavioral economics that seeks to leverage technology to collect large amounts of data to model group and social trends in large populations. Some examples include traffic patterns in a city, buying trends of specific cliques in a community, or propagation of trading information in the market. The general thesis of the course is that optimal group performance can be obtained by increasing communication within and between networks while avoiding feedback loops.
The main lectures of the course generally serve as a summary of the Instructors book (sold separately). The optional lectures tell you the types of things researchers are currently doing in this topic. The optional reading consist of 30+ research papers on the material if you want to get deeper into it.
However, from an academic standpoint this course is lacking. It does nothing more than bring awareness that this field exist, without going into any depth about how to create/collect/ or use the data or science they are talking about. There is no instruction or assessment at all in the course.