Vulnerability of social choice mechanisms to malicious influence is a long-standing concern. An increasingly important means of malicious influence involves digital media platforms through the use of fake or highly misleading information. The net effect of such influence is to change the attitudes of mechanism participants about the relative importance of issues, as well as their perception of candidates and their views and, as a consequence, change social choice outcomes. This proposal aims to develop systematic quantitative and algorithmic approaches for studying control of social choice mechanisms when manipulation targets perceptions about and views on issues. Consequently, this research has the potential to significantly contribute to the broader interdisciplinary study of vulnerability of social choice mechanisms to malicious influence.
Specifically, this research will investigate a novel model of control of social choice mechanisms which builds on the spatial theory of voting in which voters' preferences over candidates are generated based on their relative similarity on issues. In this model, the primary target of manipulation is perception of issues, both in terms of their relative importance, as well as perception of candidates' views. Algorithmically, this opens several new classes of problems with little prior research, such as the problem of issue selection, where the malicious party may select which issues are most salient, or opinion manipulation where a malicious actor aims to mislead mechanism participants about where the candidates stand on issues. Conceptually, this problem has a more direct connection to common means of subversion of social choice mechanism in reality, such as advertising and campaigning, both on social and conventional media. Furthermore, this project will study the dual problem of protecting social choice mechanisms in the spatial model, providing a series of novel modeling and algorithmic contributions for this problem.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
