2021/05/17 by Jonas Israel, Markus Brill · 1 citation
Computer Science · #cs.GT
published as Proceedings of the the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021)
arxiv created 2021/05/17 · arxiv updated 2021/05/18
Proportional ranking rules aggregate approval-style preferences of agents into a collective ranking such that groups of agents with similar preferences are adequately represented. Motivated by the application of live Q&A platforms, where submitted questions need to be ranked based on the interests of the audience, we study a dynamic extension of the proportional rankings setting. In our setting, the goal is to maintain the proportionality of a ranking when alternatives (i.e., questions) -- not necessarily from the top of the ranking -- get selected sequentially. We propose generalizations of well-known aggregation rules to this setting and study their monotonicity and proportionality properties. We also evaluate the performance of these rules experimentally, using realistic probabilistic assumptions on the selection procedure.