Dr Chico Camargo is a research associate at the Oxford Internet Institute, and at St Benet’s Hall, University of Oxford. His research interests cover the intersection of computational social science, complex systems, data science, cultural evolution, cultural sociology, and information theory.

Previously, he was a Postdoctoral Researcher in Data Science at the OII, developing and applying new computational and quantitative methods for the social sciences, focusing on the dynamics of public opinion, political volatility, agenda setting and human mobility, and on the analysis of large-scale datasets.

Chico graduated with a BSc from the University of São Paulo, as part of the Molecular Sciences Programme, and later worked in mathematical modelling in biology at the Wolfson Centre for Mathematical Biology, and at the Department of Zoology, University of Oxford. He then moved to a PhD (DPhil) in systems biology, also at Oxford, as a Clarendon Scholar in Brasenose College. In his PhD research, he used tools from complex systems and machine learning to investigate the physical principles that rule biological evolution.

You might also find Chico writing for Huffpost Brasil or for The Conversation, or making videos at BláBláLogia, an award-winning Portuguese-speaking science channel on YouTube, which is also a part of Science Vlogs Brasil.

Positions held at OII:

  • Research Associate, December 2020 –
  • Postdoctoral Researcher in Data Science, January 2018 – 2020
  • Research Assistant in Complex Networks, May 2017 – 2018

Research Interests:

computational social science, social data science, applications of machine learning, natural language processing (NLP), public opinion dynamics, complex systems,  collective behaviour, cultural evolution, digital humanities, algorithmic information theory


Current projects

  • Current Affairs 2.0: Agenda setting in the European Union

    Participants: Dr Scott Hale, Fabian Flöck, Przemyslaw Grabowicz, David Jurgens, Chico Camargo

    This project seeks to measure and explain what societal issues are given the highest priorities by media organizations, policy makers, and the general public in different nations and languages of the European Union.

Past projects

  • Mapping Playful Spaces in the Museum

    Participants: Dr Kathryn Eccles, Dr Chico Camargo

    This project seeks to use social media data to enhance our understanding of ‘playful’ behaviour across Oxford’s gardens, libraries, and museums, looking for new types of visitor engagement.

  • Political Volatility

    Participants: Professor Helen Margetts, Dr Scott Hale, Dr Chico Camargo, Dr Myrto Pantazi, Professor Peter John

    This project seeks to quantify trends and changes in the volatility of public opinion before and after widespread use of social media, and to study how social information can drive public opinion.

  • TRANSNET: Forecasting and understanding transport network resilience and anomalies

    Participants: Dr Scott A. Hale, Dr Jonathan Bright, Dr Graham McNeill, Chico Camargo

    This project seeks to utilise newly available data to help urban policy makers improve transport infrastructure to cope with growing and increasingly mobile populations.


  • Are We Really Living in an Infodemic? Deconstructing a Buzzword

    Recorded: 4 November 2020

    Duration: 00:58:56

    This webinar describes the main consequences of the uncritical adoption of the term ‘infodemic’ in the development of rigorous science on the topic, and further argues how the uncritical adoption of it in policymaking can do more harm than good.

  • Countering the COVID-19 Misinfodemic with Text Similarity and Social Data Science

    Recorded: 24 June 2020

    Duration: 01:02:23

    Dr Scott A. Hale discusses how text similarity algorithms are being used to help fact-checkers locate misinformation, cluster similar misinformation, and identify existing fact-checks on platforms with end-to-end encryption. Moderated by Dr Chico Camargo.

  • Transnet: Understanding traffic with open data and visualization

    Recorded: 26 July 2018

    Duration: 00:42:30

    This presentation, hosted by the Alan Turing Institute focuses on using crowd-sourced data, such as OpenStreetMap and Waze, to improve traffic models and better understand the factors contributing to traffic jams and other traffic issues.




Integrity Statement

My work has been financially supported by the Volkswagen foundation, the Oxford IT Innovation Challenges Panel, and by Lloyd’s Register Foundation and the Engineering and Physical Sciences Research Council (EPSRC) via the Alan Turing Institute.