CONSENSUS Project: Identifying publicly acceptable policy implementations

TL;DR

This paper presents a model that infers public preferences for policy implementations by analyzing social media or game feedback, framing policy selection as a multi-objective optimization problem.

Contribution

It introduces a novel approach combining social media analysis and game-based feedback to identify publicly acceptable policy options within a multi-objective framework.

Findings

Effective inference of public policy preferences from social media content.

A multi-objective optimization model for policy selection.

Mitigation of social objective function limitations using a black-box approach.

Abstract

Even though it is unrealistic to expect citizens to pinpoint the policy implementation that they prefer from the set of alternatives, it is still possible to infer such information through an exercise of ranking the importance of policy objectives according to their opinion. Assuming that the mapping between policy options and objective evaluations is a priori known (through models and simulations), this can be achieved either implicitly through appropriate analysis of social media content related to the policy objective in question or explicitly through the direct feedback provided in the frame of a game. This document focuses on the presentation of a policy model, which reduces the policy to a multi-objective optimization problem and mitigates the shortcoming of the lack of social objective functions (public opinion models) with a black-box, games-for-crowds approach.