
Dr Chico Camargo is an interdisciplinary researcher who develops and applies computational tools to study complex systems, collective human behaviour, public opinion dynamics and culture change.
Chico Camargo
Postdoctoral Researcher in Data Science
Profile
Dr Chico Camargo is a Postdoctoral Researcher in Data Science at the OII. He is an interdisciplinary researcher whose work consists in developing and applying new computational and quantitative methods for the social sciences, currently focusing on the dynamics of public opinion, political volatility, agenda setting and human mobility, and on the analysis of large-scale datasets. He is also very interested in using these new methods to investigate how the media environments we inhabit shape the beliefs we hold, the information we spread and the stories we tell.
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.
Position held at OII:
- Postdoctoral Researcher in Data Science, January 2018 –
- 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
Research
Current projects
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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
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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.
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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.
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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.
Videos
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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.
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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.
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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.
Events
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OII’s Wednesday Webinar Week 4 ‘Are We Really Living in an Infodemic? Deconstructing a Buzzword’
4 November 2020
Dr Chico Camargo and Felix M. Simon from the OII will discuss the term 'infodemic', and argue it's uncritical use in policy making, whilst highlighting the additional dangers of it's associated terms.
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Countering the COVID-19 Misinfodemic with Text Similarity and Social Data Science
24 June 2020
Dr Scott A. Hale will discuss how text similarity algorithms are being used to help fact-checkers locate misinformation, cluster similar misinformation, and identify existing fact-checks in the context of tip lines on platforms with end-to-end encryption
Blog
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Cutting congestion and minimising traffic disruption using online mapping data
6 March 2020
Authors: Chico Camargo
In his latest blog, OII postdoctoral researcher Dr Chico Q. Camargo explains why using data from online mapping tools can help policymakers and planners ...
Read More Cutting congestion and minimising traffic disruption using online mapping data -
Better and locally sensitive use of data could cut traffic jams
6 November 2019
Authors: Chico Camargo
Ever been stuck in queuing traffic which seems to have no explanation? Have you ever encountered a roundabout which creates more congestion than can ...
Read More Better and locally sensitive use of data could cut traffic jams
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.