In the last chapter, we looked at digital media, their characteristics, and how they are affecting politics and society. Before we will discuss these questions in greater detail in later chapters, we need to talk about how digital media have extended the options available to scientists to examine society, digital media, and the interconnection between the two. This is why we need to talk about computational social science, or CSS for short.
Computational social science (CSS) is an interdisciplinary scientific field that studies human behavior and social systems using computational methods and research practices. This includes developing and testing theoretical assumptions but also the systematic description of the behavior of people, organizations, institutions and complex socio-technical systems. A defining characteristic of CSS is the close interdisciplinary cooperation between social sciences, computer science, and natural sciences. Different research fields complement each other in the investigation of social phenomena and processes through their different perspectives and core competencies. The aim of CSS is both to understand new social phenomena triggered by digitization and to develop new perspectives on traditional research interests in social science. Both endeavors are significantly shaped by the use of new data sets and analytical methods made available through digital technology.
In this session, we will be laying some foundations for using CSS to better understand the impact of digital media on politics and society. We will discuss what the term computational social science means and what makes this approach different from other approaches in the social sciences. After this, I will walk you through a typical project pipeline in CSS. Then we are ready to talk about two prominent approaches of CSS within political science: text analysis and the work with with digital trace data.
But as a start, let's see what people mean when they talk about computational social science.