Abstract

The field of computational social science (CSS) is proliferating over the last few years. However, a comprehensive understanding of the characteristics of scientists in CSS still lacks. To address this limitation, we aim at constructing a data set dedicated to scientists in CSS by collecting data from Google Scholar (GS) and social media to map out their demographics and interactions. The self-reported research interests on GS are the main advantage compared with other bibliometric data (e.g., Web of Science), which motivates us to choose GS as our primary data source. This dataset will allow us to (i) identify the underrepresented groups in CSS concerning gender, institutions, and research fields; and (ii) quantify the patterns of scientific collaboration and social interactions of scientists in CSS with network analysis. We will provide insights and implications on building a more inclusive and diverse CSS research community.

Principal Investigators