The Diffusion of a Task Recommendation System to Facilitate Contributions to an Online Community



This paper studies the diffusion of SuggestBot, an intelligent task recommendation system that helps people find articles to edit in Wikipedia. We investigate factors that predict who adopts SuggestBot and its impact on adopters' future contributions to this online community. Analyzing records of participants' activities in Wikipedia, we found that both individual characteristics and social ties influence adoption. Specially, we found that highly involved contributors were more likely to adopt SuggestBot; interpersonal exposure to innovation, cohesion, and tie homophily all substantially increased the likelihood of adoption. However, connections to prominent, high-status contributors did not influence adoption. Finally, although the SuggestBot innovation saw limited distribution, adopters made significantly more contributions to Wikipedia after adoption than nonadopter counterparts in the comparison group.