This free workshop is an introduction to computational social science. It offers attendees a chance to understand and discuss what computational social science is, what it is good for, how to become a computational social scientist, and the basic steps to follow in an ideal computational social science research project.

Scientific research and teaching are increasingly influenced by computational tools, methods and paradigms. The social sciences are no different, with many new forms of social data only available or practical through computational means (Kitchen, 2014).

While social science research has always been marked by technological approaches to some degree, the field of computational social science involves the use of tools, data and methods that require a different skill set and mindset.

The workshop intersperses instruction with discussion and gives participants the chance to develop a research project idea through several steps. The workshop is suitable for absolute beginners and NO CODING SKILLS are required. That said, several Jupyter notebooks are provided to allow those who are interested to develop relevant coding skills through interactive exercises in their own time.

• Presenters: Louise Capener and Nadia Kennar

Kitchen, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, https://doi.org/10.1177/2053951714528481.

• Level: Any level, from absolute beginner to statistics whiz
• Experience/knowledge required: No specific knowledge required, but it will make much more sense if you currently (or plan to) conduct social science research
• Target audience: Social scientists who are interested in or confused by what computational and empirical social science is about, or who know they want to start doing more computational work but don’t know how to get started