@conference {1500402,
	title = {Controlling Elections through Social Influence},
	booktitle = {International Conference on Autonomous Agents and Multiagent Systems (AAMAS-18)},
	year = {2018},
	abstract = {Election control considers the problem of an adversary who attempts
to tamper with a voting process, in order to either ensure that their
favored candidate wins (constructive control) or another candidate
loses (destructive control). As online social networks have become
significant sources of information for potential voters, a new tool
in an attacker{\textquoteright}s arsenal is to effect control by harnessing social
influence, for example, by spreading fake news and other forms of
misinformation through online social media.
We consider the computational problem of election control via
social influence, studying the conditions under which finding good
adversarial strategies is computationally feasible. We consider two
objectives for the adversary in both the constructive and destructive
control settings: probability and margin of victory (POV and MOV,
respectively). We present several strong negative results, showing,
for example, that the problem of maximizing POV is inapproximable
for any constant factor. On the other hand, we present approximation algorithms which provide somewhat weaker approximation
guarantees, such as bicriteria approximations for the POV objective
and constant-factor approximations for MOV. Finally, we present
mixed integer programming formulations for these problems. Experimental results show that our approximation algorithms often
find near-optimal control strategies, indicating that election control
through social influence is a salient threat to election integrity.},
	author = {Bryan Wilder and Vorobeychik, Yevgeniy}
}
