Rick currently works on research with Dr. Neil Johnson’s research group, studying the many-body physics of online extremism. His personal contribution is the application of several machine learning techniques to content shared in these sites.

Find his work on ORCID.

He is co-author on the following papers (all links are DOIs):

• How U.S. Presidential elections strengthen global hate networks, 10/29/24
• Adaptive link dynamics drive online hate networks and their mainstream influence, 4/17/24
• Controlling bad-actor-artificial intelligence activity at scale across online battlefields, 1/23/24
• Offline Events and Online Hate, 1/25/23
• Dynamic Topic Modeling Reveals Variations in Online Hate Narratives, 7/7/22
• Connectivity Between Russian Information Sources and Extremist Communities Across Social Media Platforms, 6/22/22
• Machine Learning Reveals Adaptive COVID-19 Narratives in Online Anti-Vaccination Network, 3/29/22
• Dynamic Latent Dirichlet Allocation Tracks Evolution of Online Hate Topics, 2/24/22
• How Social Media Machinery Pulled Mainstream Parenting Communities Closer to Extremes and their Misinformation during Covid-19, 12/27/21
• Machine Learning Language Models: Achilles Heel for Social Media Platforms and a Possible Solution, 12/23/21
• Online hate network spreads malicious COVID-19 content outside the control of individual social media platforms, 6/15/21
• Hidden order across online extremist movements can be disrupted by nudging collective chemistry, 5/19/21
• Quantifying COVID-19 Content in the Online Health Opinion War Using Machine Learning, 5/11/20