SOC41070

The ongoing digital transformation of our societies has had quite a few “biproducts”, among them is the unprecedented amount of transactional digital data that we produce as we go about our daily lives, also known as big data. Big Data are being used to study the very same digital transformation that led to their generation, as well as more general and fundamental aspects of our social lives in the framework of computational social science and beyond.
From the sociology point of view, a very first question to ask would be about the relevance of social theory to the “digitalized” study of humans. Some of the fundamental concept and theories in social studies were developed even before empirical sociology had become fashionable. Are those theories still relevant when machine learning is slowly becoming a common item in the toolset of social scientists? How social theory is being challenged, modified, and even ignored in our modern approach to studying humans and societies? How social theory can shape and motivate computational social science research? In this module, we seek to answer these questions through a short review of the main key concepts in sociology followed by an extended discussion on how they can be materialised and deployed in data-driven research through reviewing examples of successful and unsuccessful research programmes and analytical discussions.