Daniel Gayo-Avello @ the University of Oviedo

Associate professor in the Department of Computer Science at the University of Oviedo

Daniel Gayo-Avello's main area of interest is Web IR but he has been focused on social media research from the early 2010s, publishing in CACM, IEEE Internet Computing, or IEEE Multimedia. He acted as guest co-editor for a special issue of Internet Research on the predictive power of social media, contributed a chapter on Political Opinion to "Twitter: A Digital Socioscope", and coauthored the book "Retooling Politics: How Digital Media Are Shaping Democracy", published by Cambridge University Press. From March 2023 he is part of ActEU, a EU-funded research project to strengthen trust in democracy.

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Latest updates

December, 2025 (forthcoming)

"Handbook of Computational Social Science"

Edward Elgar Publishing will soon release this volume edited by Taha Yasseri. I contribute to the book with the chapter “Social media and electoral prediction: ten years after”, co-authored with Andreas Jungherr and Gonzalo Rivero, in which we revisit a decade of research on electoral prediction using social media. The book, now available for pre-order, offers a comprehensive and forward-looking overview of computational approaches in the social sciences.

November 27, 2025

"Los algoritmos de X pueden alterar la polarización afectiva"

Un nuevo estudio publicado en Science demuestra que la “curación” algorítmica del feed de X/Twitter puede aumentar o reducir la polarización afectiva de los usuarios según la exposición a mensajes hostiles. La Vanguardia se ha hecho eco del trabajo y recoge mis declaraciones sobre la importancia de estudiar el impacto de los algoritmos sin necesidad de cooperación de las plataformas y cómo los resultados de este estudio desafían investigaciones previas sobre Facebook e Instagram que sugerían un efecto mínimo de los algoritmos sobre la polarización.

July 31, 2025

"Scraping Political Narratives in 10 EU Countries"

At the ActEU Mid-Term Conference I presented a large-scale web scraping dataset to analyze political and cultural discourse across 10 EU countries. The dataset includes news articles, tweets, and Telegram posts, with a focus on climate, gender, and migration. Using automated annotation and machine learning, it offers a valuable resource for studying polarization, public trust, and online narratives.