Ranking Designs and Users in Online Social Networks.

This work-in-progress presents a new algorithm that leverages social network structure to rank designs and users in online design communities. The algorithm is based on the intuition that the importance of a design should depend on the rank of the users that created and promoted it, and the importance of a user should depend on the rank of the designs he creates and promotes in turn. The algorithm produces design rankings that are positively correlated with existing social metrics such as number of likes, but also allows designs with second-order social import to rise through the ranks. We demonstrate that the algorithm converges, and analyze the rankings it produces on both simulated and scraped social design networks.