---
title: "Dynamic Proportional Rankings"
authors:
  - "Jonas Israel"
  - "Markus Brill"
doi: "10.24963/ijcai.2021/37"
url: "https://ijcai.org/proceedings/2021/37"
pdf: "https://ijcai.org/proceedings/2021/0037.pdf"
venue: "Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"
year: 2021
pages: "261-267"
track: "Main Track"
keywords:
  - "Agent-based and Multi-agent Systems: Computational Social Choice"
  - "Agent-based and Multi-agent Systems: Voting"
---

# Dynamic Proportional Rankings

Jonas Israel, Markus Brill

*Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence*, pages 261-267. DOI: [10.24963/ijcai.2021/37](https://doi.org/10.24963/ijcai.2021/37)

## Abstract

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.