Visualizing Paired Image Similarity in Transformer Networks
The lack of explainability or interpretability is often cited as one of the main drawbacks of deep neural networks used in computer vision and machine learning.
Journal Articles & Working Papers
Efforts to contain the COVID-19 pandemic have been complicated by a parallel infodemic, defined as an overabundance of information, including misinformation, which occurs during a disease outbreak.
Viruses, Vaccines, and COVID-19: Explaining and Improving Risky Decision-making
Throughout the COVID-19 pandemic, risky decision-making has determined its trajectory, from deciding whether to socially distance or wear a mask to whether to get vaccinated.
Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares
The World Health Organization has deemed antibiotic resistance, which is primarily caused by antibiotic overuse, to be one of the world's most pressing health problems.
“We Don’t Know” Means “They’re Not Sure”
The most familiar approach to handling respondent uncertainty about survey questions, the “don’t know” (DK) response, has an inconvenient feature.
Misinformation or Activism: Mapping Networked Moral Panic Through An Analysis of #SAVETHECHILDREN
When looking at the recent social-political history of America it is difficult to avoid references to QAnon, a widespread, conservative-leaning conspiracy that amalgamates numerous conspiracies into...
Little evidence exists on the global effectiveness, or lack thereof, of potential solutions to misinformation.
Internet interventions are effective for smoking cessation and a recommended treatment approach.
Text messaging (SMS) smoking cessation programs can reach a large amount of cigarette smokers and are effective in increasing quit rates, but their efficacy has not yet been explored in Vietnam.
Trump sympathy in the Balkans: cross-border populist appeal
Do populist leaders tend to win support from the same kinds of people abroad as they do at home?