TL;DR
This paper proposes formal definitions and two modeling approaches for fake news, analyzing its effects on elections and demonstrating that awareness of fake news circulation can reduce its impact.
Contribution
It introduces a clear definition of fake news and two novel modeling frameworks for understanding its influence on electoral processes.
Findings
Qualitative understanding of fake news effects at a macroscopic level
Simulation shows awareness of fake news circulation mitigates its impact
Two modeling approaches provide insights into voter behavior and collective dynamics
Abstract
Over the past decade it has become evident that intentional disinformation in the political context -- so-called fake news -- is a danger to democracy. However, until now there has been no clear understanding of how to define fake news, much less how to model it. This paper addresses both of these issues. A definition of fake news is given, and two approaches for the modelling of fake news and its impact in elections and referendums are introduced. The first approach, based on the idea of a representative voter, is shown to be suitable for obtaining a qualitative understanding of phenomena associated with fake news at a macroscopic level. The second approach, based on the idea of an election microstructure, describes the collective behaviour of the electorate by modelling the preferences of individual voters. It is shown through a simulation study that the mere knowledge that fake news…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
