Big Data under the Microscope and Brains in Social Context: Integrating Methods from Computational Social Science and Neuroscience. Issue 1 (May 2015)

• Record Type: Journal Article
• Authors: O'Donnell, Matthew Brook; Falk, Emily B.
• Editors: Shah, Dhavan V.; Cappella, Joseph N.; Neuman, W. Russell
• Is Part Of: Annals of the American Academy of Political and Social Science. Volume 659:Issue 1(2015:May)
• Page Start: 274
• Page End: 289
• Publication Date: 2015-05
• Subjects: fMRI -- neuroscience -- social network analysis -- linguistic analysis -- natural language processing -- big data -- computational social science; Social sciences -- Periodicals; Social sciences -- United States -- Periodicals; Political science -- Periodicals; United States -- Politics and government -- Periodicals; 300
• DOI: 10.1177/0002716215569446
• Languages: English
• ISSNs: 0002-7162

Abstract

Methods for analyzing neural and computational social science data are usually used by different types of scientists and generally seen as distinct, but they strongly complement one another. Computational social science methodologies can strengthen and contextualize individual-level analysis, specifically our understanding of the brain. Neuroscience can help to unpack the mechanisms that lead from micro- through meso- to macro-level observations. Integrating levels of analysis is essential to unified progress in social research. We present two example areas that illustrate this integration. First, combining egocentric social network data with neural variables from the "egos" provides insight about why and for whom certain types of antismoking messages may be more or less effective. Second, combining tools from natural language processing with neuroimaging reveals mechanisms involved in successful message propagation, and suggests links from microscopic to macroscopic scales.