Motivating Expert Contributions to Public Goods: A Personalized Field Experiment on Wikipedia
We use a large-scale personalized field experiment on Wikipedia to examine the effect of motivation on the contributions of domain experts to public goods. Experts are 13% more interested in contributing when we mention the private benefit of contribution, such as the likely citation of their work, together with the social impact of the public good. Furthermore, we find that greater matching accuracy between a recommended Wikipedia article and an expert's paper abstract, measured by cosine similarity, increases both contribution quantity and quality. Our results show the potential of scalable personalized interventions using recommender systems to study drivers of prosocial behavior.