http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
How to situate big data in social scientific thought
As our social life is mediated by digital interfaces such as Twitter, TikTok, and Google Maps, these services are at the same time producing large quantities of social data that are transforming the social sciences. Such "Big Data" are giving researchers access to new ways of studying society, bringing the emergence of a rapidly growing discipline: Computational Social Science (CSS). Big Data are however not only bringing social scientists promises of new insights, but also important new challenges. Big Data has proven challenging to situate in existing social scientific theory, leading some to criticize CSS for seeking merely surface-level description. In this guide, we look closer at the nature of Big Data, to examine how we can better situate its study in social scientific thinking. What are we actually studying when we are studying Big Data? How do we link our findings to existing social scientific theory? We will propose a way of answering these questions, to guide aspiring social scientists who are interested in doing digital research. The guide proposes a form of CSS that is critical and pluralist, combining computational methods and Big Data with theory to critically examine how platforms are reshaping social life.
Information theory in the social sciences
Théorie de l'information en sciences sociales
SAGE research methods: doing research online