April 25, 2024, 7:42 p.m. | Cristian Rojas, Frank Algra-Maschio, Mark Andrejevic, Travis Coan, John Cook, Yuan-Fang Li

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.15673v1 Announce Type: new
Abstract: Misinformation about climate change poses a significant threat to societal well-being, prompting the urgent need for effective mitigation strategies. However, the rapid proliferation of online misinformation on social media platforms outpaces the ability of fact-checkers to debunk false claims. Automated detection of climate change misinformation offers a promising solution. In this study, we address this gap by developing a two-step hierarchical model, the Augmented CARDS model, specifically designed for detecting contrarian climate claims on Twitter. …

abstract arxiv automated cards change checkers climate climate change cs.lg false however machine machine learning media misinformation platforms prompting social social media social media platforms strategies threat twitter type

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US