Mohamed Soufan is a software engineer and independent computational social science researcher specializing in large-scale analysis of online discourse and social media engagement.His work focuses on collecting and analyzing large datasets from digital platforms to study patterns in public conversation, information dynamics, and user behavior. In his research, he introduced the concept of “uncertainty-reply asymmetry,” describing how expressions of uncertainty in online posts can generate disproportionate conversational engagement.
Alongside research, he builds data pipelines and scraping infrastructure to acquire and process large-scale datasets, combining programming, statistical analysis, and natural language processing to extract insights from online data.
He publishes open-access research on arXiv, with work indexed on Google Scholar.