The following was adapted from this Santa Fe blog post.
At a recent presentation at the Science Writers 2020 conference, Joshua Garland and Mirta Galesic of the Santa Fe Institute presented the first large-scale analysis of tens of millions of instances of hate and counter-hate speech on Twitter. Their findings suggest that organized movements to counteract hate speech on social media are more effective than striking out on one’s own.
“I’ve seen this big shift in civil discourse in the last two or three years towards being much more hateful and much more polarized,” says Garland, a mathematician and Applied Complexity Fellow at SFI. “So, for me, an interesting question was: what’s an appropriate response when you’re being cyber-bullied or when you’re receiving hate speech online? Do you respond? Do you try to get your friends to help protect you? Do you just block the person?”
To study such questions scientifically, researchers must first have access to a wealth of real-world data on both hate speech and counter-speech, and the ability to distinguish between the two. The result was a dataset of unprecedented size that allows the researchers to analyze not just isolated instances of hate and counter-speech, but also compare long-running interactions between the two.
As part of the rollout of the 2020 Computing Research Associations (CRA) Quadrennial Papers, the Computing Community Consortium (CCC) publish a paper called An Agenda for Disinformation Research. This paper, written by Joshua Garland as well as Nadya Bliss (Arizona State University), Elizabeth Bradley (University of Colorado, Boulder), Filippo Menczer (Indiana University), Scott W. Ruston (Arizona State University), Kate Starbird (University of Washington), and Chris Wiggins (Columbia University), describes a multi-disciplinary research agenda incorporating disinformation detection, education, measurements of impact, and a new common research infrastructure to combat disinformation and its effects upon the US and the world. See the full paper here.
