Computational Social Choice Meets Databases

TL;DR

This paper introduces a new framework connecting computational social choice with database systems, enabling complex queries about voting and candidates with formal semantics and complexity analysis.

Contribution

It provides a formal semantics for social choice queries in databases and analyzes the computational complexity of determining necessary answers for conjunctive queries.

Findings

Complexity results for necessary answers of conjunctive queries with positional scoring rules.

Contrast between complexity of necessary answers and necessary winners.

Framework enables sophisticated social choice queries within a database context.

Abstract

We develop a novel framework that aims to create bridges between the computational social choice and the database management communities. This framework enriches the tasks currently supported in computational social choice with relational database context, thus making it possible to formulate sophisticated queries about voting rules, candidates, voters, issues, and positions. At the conceptual level, we give rigorous semantics to queries in this framework by introducing the notions of necessary answers and possible answers to queries. At the technical level, we embark on an investigation of the computational complexity of the necessary answers. We establish a number of results about the complexity of the necessary answers of conjunctive queries involving positional scoring rules that contrast sharply with earlier results about the complexity of the necessary winners.