When people use the internet, they leave behind traces of their political behaviors and social interactions across space and time. While these digital traces are typically created and collected by businesses and governments for their own internal purposes, they are often available to researchers either incidentally or explicitly on behalf of these organizations. Digital trace data have the potential to broaden the scope and scale of political and social research, but require knowledge of computational tools and methods that are typically not taught to social scientists. Moreover, digital trace data present new legal and ethical considerations, since they often contain sensitive, individual-level information. Digital trace data also present conceptual challenges, some which are not new to political and social scientists, like representativeness, and others that are unique to the web, including algorithmic confounding.
Data Types: Numerical, Categorical, Networks, Text
Methods: Network analysis, Descriptive statistics, Data management, Visualization, Machine learning
Substantive Areas: Science/Reproducibility, Web/Social Media
Programming Languages: R, Unix, Git