  Isolated silos of scientific research and the growing challenge of
information overload limit awareness across the literature and hinder
innovation. Algorithmic curation and recommendation, which often prioritize
relevance, can further reinforce these informational "filter bubbles." In
response, we describe Bridger, a system for facilitating discovery of scholars
and their work. We construct a faceted representation of authors with
information gleaned from their papers and inferred author personas, and use it
to develop an approach that locates commonalities and contrasts between
scientists to balance relevance and novelty. In studies with computer science
researchers, this approach helps users discover authors considered useful for
generating novel research directions. We also demonstrate an approach for
displaying information about authors, boosting the ability to understand the
work of new, unfamiliar scholars. Our analysis reveals that Bridger connects
authors who have different citation profiles and publish in different venues,
raising the prospect of bridging diverse scientific communities.
