How do people manage and leverage their networks for career advancement in times of uncertainty caused by punctuated career events (e.g., M&A, natural disasters, political/industrial shocks)? How do those formations and uses of social connections affect the broader structure and functionality of networks in labor markets?
Drawing on available online data sources (e.g., LinkedIn, Twitter, Sansan), the current project aims to identify individuals who experience job-related instability, detect their responses as changes in networking and communication behavior, estimate the effect that these changes have on an individual’s career mobility, and model how the change in networking behavior affects the macro structure of professional communication networks.
The project will contribute to a broader understanding of the actual heuristics people use in leveraging their networks and of the global network’s overall functionality in supporting the optimal functioning of labor markets. We will leverage the heterogeneity of observed networks along with computationally simulated counterfactuals to explore the variation in the ability of individuals to find new jobs, thus capturing the extent to which less clustering, more connections, or more bridging links would lead to better labor market outcomes.