Research focus
I study misinformation engagement from its earliest signals through social response to causal influence. My research combines sequence modeling, behavioral theory, and counterfactual analysis to understand propagation.
The first signals illuminate a possible propagation path.
Featured research
Each project asks a different question about the same process: where engagement is heading, what drives it, and which outside signals change it.
How early can we forecast a post’s reach?
IC-Mamba uses a state-space model with temporal embeddings to learn from irregular, interval-censored engagement observations. It forecasts how likes, shares, comments, and broader narratives develop before a trajectory is fully visible.
Why do people engage with misinformation?
DREAMS draws on social exchange theory to model engagement as an evolving interaction between user effort, social reward, and platform context. It learns how emotional and contextual signals shape engagement across platforms.
What actually changes the spread?
CITRUS uses a joint treatment-outcome framework to estimate how external signals—such as search trends, news coverage, and influencer activity—change misinformation engagement. Counterfactual comparisons help separate causal influence from simple correlation.
DREAMS across platforms
The study spans 2.37 million posts from 2021–2025.
See the full publication list on my Google Scholar profile.
