معرفی
Xuanjun (Jason) Gong is an Assistant Professor in the Department of Communication and Journalism at Texas A&M University. His research program bridges computational modeling, media psychology, and neuroscience to investigate sequential media selection, information diffusion, and neural correlates of media engagement. He employs diverse methodologies including fMRI, behavioral experiments, and large-scale social media analysis.
Gong's research focuses on the computational mechanisms of media choice, exploring how curiosity, mood, and cognitive processes shape decisions in dynamic media environments. His work formalizes theories like mood management and flow states using drift-diffusion models and network neuroscience approaches. Key themes include prediction of media behaviors, cross-platform information spread, and neurocognitive foundations of audience engagement.
His publications demonstrate consistent emphasis on developing integrative frameworks that combine communication theory with computational rigor. Recent work advances understanding of time-dependent media selection, neural dynamics during flow experiences, and social media discourse patterns during exogenous events. Gong's research has been recognized with a Graduate Student Award (CNS21).
Awards & Honors:
- Graduate Student Award, CNS21 (2021)
