The ANNALS of the American Academy of Political & Social Science
Toward Computational Social Science: Big Data in Digital Environments
- Dhavan V. Shah - University of Wisconsin-Madison, USA
- Joseph N. Cappella - University of Pennsylvania, USA
- W. R. Neuman - New York University, Steinhardt School of Education
The exponential growth of structured and unstructured social data has confronted fields such as political science, sociology, psychology, information systems, public health, public policy, and communication with a unique challenge: How can scientists best use computational tools to analyze such data, problematical as they may be, with the goal of understanding individuals and their interactions within social systems? The unprecedented availability of information on discrete behaviors, social expressions, personal connections, and social alignments provides insights on a range of phenomena and influence processes — from personality traits to political behaviors; from public opinion to relationship formation — despite issues of representativeness and uniformity. This volume explores some of the key issues confronting researchers who pursue computational social science in the age big data.