Recruitment on Networks: Cost, Risks, and Uncertainty

March 7, 2018

What is the nature of recruitment and what kind of new dimensions does it include when recruited actors are supposed to be engaged in high-risk activities?

Cory Cox, PhD candidate at the Center for Network Science investigates these questions among many others by examining numerous recruiting organizations.

Using the Watts-Dodds-Newman Model (2002) on search and identity in social networks as a starting point, he re-conceptualizes crucial concepts such as risk and uncertainty in order to elaborate a comprehensive model on recruitment processes that reflects real-world situations.

Cory identifies risk as anticipated danger and asks whether risk-taking calculations are different when risk is coupled with uncertainty. Starting from the models on searchable networks having short path, through the examination of conceptual distance (by mapping social hierarchical groups), social identity, tie strength and local information theories, he identifies the key features of Recruitment Search, for example, the partly specified target actors with rank-ordered attributes as a consequence of the non-topological, local information and search query performance on social networks.

Cory also takes into account mesoscopic level implications assuming that risk sharing involves coordinated action in a group environment where available strong ties play an important role in group solidarity. Besides, he hypothesizes that in the case of high uncertainty, path dependency is also an emerging phenomenon expanding the dimensionality of the recruitment process.

Recruiting organizations (not only social movements) have to find the balance between recruiting socially similar clusters and being diverse since both practices are crucial to a generative functioning.

Cory plans to further extend his research by designing a query refinement dynamic based on the information retrieval literature; gaining new insights from information and computer scientific theories and interrogating several datasets on video games and military enlistments.

Blog post by Rebeka O. Szabó