This afternoon I will give a research talk at the Institute of Communication and Media Research at the University of Zurich.
Computational Communication Science promises to give new insight into communication and social behavior by using digital methods to study large and heterogeneous data sets consisting of traces left by online activity from Instagram posts, comments to online news articles on various sites to online purchases.
This talk focuses on the tools needed to carry out this research. In particular, we need tools to gather data, such as digital trace data; analyze the resulting texts, networks, and images to measure our theoretical quantities; and store and share the data and results. In all cases, it is important to focus on the replicability, validity, and transparency of data, analytic processes, and results. In this talk, I will outline the requirements, existing resources and challenges for “open” Computational Communication Science. For each of these steps, I will discuss the possibilities and limitations of existing tools, and describe the methods and open sources tools that we are currently developing. I will call for a turn to “open science” and collaboration on open source software to build the tools we need to develop Computational Communication Science.