We use a large-scale field experiment on Wikipedia to examine the effect of motivation on the contributions of domain experts to public information goods. We find that experts are more interested in contributing when we mention the private benefit of contribution, such as the likely citation of their work. More importantly, using cosine similarity, we find that greater matching accuracy between a recommended Wikipedia article and an expert's paper abstract increases both contribution quantity and quality. Our results show the potential of combining machine learning tools with field experiments to study drivers of prosocial behavior.