ERC Consolidator Grant · 2022
Bayesian Gaussian Processes. Or: How I Learned to Stop Worrying and Love Nonlinear Social Science
Nonlinearity is ubiquitous in the social sciences. In cross-sectional research, nonlinearity naturally follows from the fact that variables often depend on human perception. The tendency to share fake news, for example, depends in a complex nonlinear manner on peoples’ personality and political preferences. In longitudinal research, nonlinearity follows from the fact that temporal social processes are nonstationary by nature. For instance, stressful life events (e.g., unemployment, pandemic) have a complex nonlinear impact on well-being over time. To study these nonlinear phenomena, much more data are needed than in linear analyses. Therefore, researchers increasingly rely on technological…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.