This study aims to minimize the influence of fake news on social networks by deploying debunkers to propagate true news. This is framed as a reinforcement learning problem, where, at each stage, one user is selected to propagate true news. A challenging issue is episodic reward where the "net" effect of selecting individual debunkers cannot be discerned from the interleaving information propagation on social networks, and only the collective effect from mitigation efforts can be observed. Existing Self-Imitation Learning (SIL) methods have shown promise in learning from episodic rewards, but are ill-suited to the real-world application of fake news mitigation because of their poor sample efficiency. To learn a more effective debunker selection policy for fake news mitigation, this study proposes NAGASIL - Negative sampling and state Augmented Generative Adversarial Self-Imitation Learning, which consists of two improvements geared towards fake news mitigation: learning from negative samples, and an augmented state representation to capture the "real" environment state by integrating the current observed state with the previous state-action pairs from the same campaign. Experiments on two social networks show that NAGASIL yields superior performance to standard GASIL and state-of-the-art fake news mitigation models.

On Monday, as Americans considered the possibility of a Donald Trump indictment and a presidential perp walk, Eliot Higgins brought the hypothetical to life. Higgins, the founder of Bellingcat, an open-source investigations group, asked the latest version of the generative-AI art tool Midjourney to illustrate the spectacle of a Trump arrest. It pumped out vivid photos of a sea of police officers dragging the 45th president to the ground. He generated a series of images that became more and more absurd: Donald Trump Jr. and Melania Trump screaming at a throng of arresting officers; Trump weeping in the courtroom, pumping iron with his fellow prisoners, mopping a jailhouse latrine, and eventually breaking out of prison through a sewer on a rainy evening. The story, which Higgins tweeted over the course of two days, ends with Trump crying at a McDonald's in his orange jumpsuit. All of the tweets are compelling, but only the scene of Trump's arrest went mega viral, garnering 5.7 million views as of this morning.