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Changing institution is a scientist's key career decision, which plays animportant role in education, scientific productivity, and the generation ofscientific knowledge. Yet, our understanding of the factors influencing arelocation decision is very limited. In this paper we investigate how thescientific profile of a scientist determines their decision to move (i.e.,change institution). To this aim, we describe a scientist's profile by threemain aspects: the scientist's recent scientific career, the quality of theirscientific environment and the structure of their scientific collaborationnetwork. We then design and implement a two-stage predictive model: first, weuse data mining to predict which researcher will move in the next year on thebasis of their scientific profile; second we predict which institution theywill choose by using a novel social-gravity model, an adaptation of thetraditional gravity model of human mobility. Experiments on a massive datasetof scientific publications show that our approach performs well in both thestages, resulting in a 85% reduction of the prediction error with respect tothe state-of-the-art approaches.

Prediction of next career moves from scientific profiles