Influence flows in the academy: Using affiliation networks to assess peer effects among researchers

Little is known about how influence flows in the academy, because of inherent difficulties in collecting data on large samples of friendship and advice-seeking networks over time. We propose taking advantage of the relative abundance of “affiliation network” data to assess aggregate patterns of how individual and dyadic characteristics channel influence among researchers. We formulate and test our approach using new data on 2034 faculty members at Stanford University over a 15-year period, analyzing different affiliations as potential influence channels for changes in grant productivity. Results indicate that research productivity is more malleable to ongoing interpersonal influence processes than suggested in prior research: a strong, salient tie to a colleague in an authority position is most likely to transmit influence, and most forms of influence are likely to spill over to behaviors outside those jointly produced by collaborators. However, the genders and institutional locations of ego-alter pairs significantly affect how influence flows.