Daniel Loiola is a research scientist and media researcher with eight years of experience studying how digital platforms shape information, misinformation, and sociotechnical imaginaries. He pairs rigorous academic training (PhD in Communication Science, visiting research at Politecnico di Milano) with hands-on engineering skills—building large-scale Python crawlers, FastAPI pipelines and Elasticsearch systems that have scaled data collection to millions of items for disinformation monitoring. His work blends digital methods, data visualization and platform studies, having developed novel bot-based experiments on YouTube recommendation bubbles and contributed to international data sprints analyzing political communications. Daniel has translated research into practical tools and workshops that make computational methods accessible to non-technical humanists and journalists. He is equally comfortable in academic publishing and operational deployments for newsrooms and NGOs, evidenced by collaborations with media partners like Rede Globo and Open Knowledge Brasil. A distinctive strength is his ability to move between theory and production: designing critical, STS-informed research while shipping reliable data infrastructure used in real-world investigations.
9 years of coding experience
9 years of employment as a software developer
Visiting Scholar (PhD) Design, Visiting Scholar (PhD) Design at Politecnico di Milano
Data Foundations Nanodegree, Data Foundations Nanodegree at Udacity
Pós-graduação em Comunicação Digital, Pós-graduação em Comunicação Digital at PUC Minas
Doctor of Philosophy (PhD) - Communication Science, Doctor of Philosophy (PhD) - Communication Science at Universidade Federal de Minas Gerais
Contributions:26 pushes, 1 branch in 7 years 3 months
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