Tutorial for IC2S2 2019
The science of science is an emerging field that uses computational tools to quantify the patterns underlying scientific relationships and dependencies from the explosion of data in science. In this tutorial, we aim to provide a comprehensive overview of the field, including recent studies on scientific ideas, individual careers and teams from the perspective of computational social science.
Considering the complex and apparently unpredictable nature of a scientific career, we will answer the following questions: are there reproducible patterns underlying an individual career in science? What are the fundamental mechanisms that drive the success of a scientist? Accurate quantitative answers to these questions are the aim of this tutorial, as they can affect both the way we train scientists and the way we acknowledge and reward scientific excellence.
Scientists do not work alone. The modern science has been shifted toward big science dominated by team productions. In this tutorial, we will rely on a rich body of literature that is often called the Science of Team Science (SciTS), and discuss how scientists collaborate and work together in teams. We will address the questions like why are some collaborations so fruitful, lasting, and impactful while others fail, at times, spectacularly? What are the factors that help and hinder the effectiveness of teams?
New scientific ideas do not emerge in vacuum. They inherently build on previous work by other scientists. In return, researchers give credit to body of work their ideas built on, giving rise to what we call today citations. As such, modeling the emergence and spreading of scientific ideas through citation networks has been widely studied in recent years. This part of the tutorial will discuss recent studies on the dynamics of scientific ideas through citation networks and the underlying mechanisms.