(with some content based on materials prepared by Dan Cervone, Alex Hanna, Ken Benoit, Paul Nulty, Kevin Munger, and Justin Grimmer.)
Citizens across the globe spend an increasing proportion of their daily lives online. Their activities leave behind granular, time-stamped footprints of human behavior and personal interactions that represent a new and exciting source of data to study standing questions about political and social behavior. At the same time, the volume and heterogeneity of web data present unprecedented methodological challenges. The goal of this course is to introduce participants to new computational methods and tools required to explore and analyze Big Data from online sources using the R programming language. We will focus in particular on data collected from social networking sites, such as Facebook and Twitter, whose use is becoming widespread in the social sciences.
There are two ways you can follow the course and run the code contained in this GitHub repository. The recommended method is to connect to the provided RStudio server where all the R packages have already been installed, and all the R code is available. To access the server, visit bigdata.pablobarbera.com and log in with the information provided during class.
Alternatively, you can run the code in your own laptop. You will need R and RStudio installed. Given the number of attendants, I will not be able to provide support during the course, but feel free to email me later if you have any issue.
If you're using your own laptop, you can either download the course materials clicking on each link in this repository, download it as a zip file, or you can "clone" it, using the buttons found to the right side of your browser window as you view this repository. If you do not have a git client installed on your system, you will need to get one here and also to make sure that git is installed.
You can also subscribe to the repository if you have a GitHub account, which will send you updates each time new changes are pushed to the repository.