Lies, Bullshit and Fake News

Truth, Lies and Bullshit distinguishing classes of dishonesty

In this paper, we distinguish three important classes of dishonesty that can occur in multi-agent systems, as well as in human society. In particular, the distinction is being made between lies and bullshit, following the work of Harry Frankfurt. The difference is that someone who tells a lie has access to the truth, whereas the concept of bullshit requires no knowledge of the truth at all. Tha...

Fake News in Social Networks

We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in a piece of news, which itself may be either true or false. Agents base their decision on a private signal and their neighbors’ past actions. Given these inputs, agents follow strategies derived via multi-agent deep reinforcement learning and receive utility from acting in acco...

The Economics of "Fake News"

Automatic Detection of Fake News

The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online...

Alt-News and Post-Truths in the "Fake News" Era