I would argue that computational social science necessitates collaboration, and indeed is tamed by it. A collaborative approach provides the necessary structure, goals, and a critical approach to research methods. In response to the question of what computational social science has helped me achieve, it may seem obvious to mention the concrete projects, the outputs, the measurable outcomes. However, for me computational social science has achieved something more substantial and enduring—a new way of working, a new way of thinking, and a new kind of enthusiasm for research.

Watch our panel event from the ESRC Festival of Social Science on what skills social scientists will need to be able to do the social research of the future.

Calling all social scientists. How were you trained? How are you keeping up (or not) with new developments in this rapidly changing digital world? How are you training your students?

This was the subject of an event sponsored by SAGE Ocean as part of the ESRC’s 2018 Festival of Social Science. In case you are not aware, Sage, who have been at the forefront of publishing qualitative work, have now launched SAGE Ocean – an initiative “to help social scientists to navigate vast datasets and work with new technologies”.

Being a data scientist with a sociological background is extremely valuable in trying to answer research questions to advance contemporary humanity. It goes beyond programming skills or just applying algorithms to data.