The Complexity of Social Coordination

TL;DR

This paper extends the class of feasible entangled queries for data-driven social coordination, providing efficient evaluation algorithms for broader scenarios and demonstrating their practicality through experiments.

Contribution

It introduces methods to evaluate safe entangled queries without the uniqueness constraint and algorithms for coordination on shared attributes without safety.

Findings

Efficient evaluation of safe entangled queries without the uniqueness constraint.

Algorithms for coordination on shared attributes without safety.

Experimental results show feasibility across various scenarios.

Abstract

Coordination is a challenging everyday task; just think of the last time you organized a party or a meeting involving several people. As a growing part of our social and professional life goes online, an opportunity for an improved coordination process arises. Recently, Gupta et al. proposed entangled queries as a declarative abstraction for data-driven coordination, where the difficulty of the coordination task is shifted from the user to the database. Unfortunately, evaluating entangled queries is very hard, and thus previous work considered only a restricted class of queries that satisfy safety (the coordination partners are fixed) and uniqueness (all queries need to be satisfied). In this paper we significantly extend the class of feasible entangled queries beyond uniqueness and safety. First, we show that we can simply drop uniqueness and still efficiently evaluate a set of safe entangled queries. Second, we show that as long as all users coordinate on the same set of attributes, we can give an efficient algorithm for coordination even if the set of queries does not satisfy safety. In an experimental evaluation we show that our algorithms are feasible for a wide spectrum of coordination scenarios.