Focusing the macroscope: how we can use data to understand behavior
Individual decisions can have a large impact on society as a whole. This is obvious for political decisions, but still true for small, daily decisions made by common citizens. Individuals decide how to vote, whether to stay at home when they feel sick, to drive or to take the bus. In isolation, these individual decisions have a negligible social outcome, but collectively they determine the results of an election and the start of an epidemic. For many years, studying these processes was limited to observing the outcomes or to analyzing small samples. New data sources and data analysis tools have created a "macroscope" and made it possible to start studying the behavior of large numbers of individuals, enabling the emergence of large-scale quantitative social research. At the Data Science and Policy (DS&P) research group we are interested in understanding these decision-making events, expecting that this deeper knowledge will lead to a better understanding of human nature, and to improved public decisions.
In the past, we have been focusing mainly on three types of problems, strongly dependent on both the behaviors of individuals (in what we call bottom-up collective processes), and of decision-makers (the top-down decisions). The first is related with what we usually identify as political debate and deliberation and we have computationally analyzed the past 40 years of debates in the Portuguese Parliament. The second is disease dynamics, of both infections and non-infectious diseases, and we try to improve nowcasting and forecasting of several diseases and reduce antibiotic over-prescription. The third is much more fundamental and it comes from the realization that the Digital Era is offering us a giant mirror, a macroscope, that will allow us to understand human behavior at a completely new scale. By using both social networks and the spread of fake news as case studies, we are trying to identify underlying principles, both mathematical and behavioral, that can be generalized to different contexts.
In parallel, and recognizing that these tools might also have a very negative impact on society, we try to raise public awareness of these risks and involve citizens in the definition of appropriate ethical guidelines and legislation.During the talk I will briefly describe some of these past projects and offer examples of how we can use data science to study psychology and human behavior. At the net, I will present new ideas in distributed computing and how it can help us in privacy protection.
20/11/2019 16:00
Multimodal Systems
Joana Gonçalves de Sá is an Associate Professor at Nova School of Business and Economics, Universidade Nova de Lisboa and the leader of the Data Science and Policy research group. Before that, she was a Principal Investigator at the Instituto Gulbenkian de Ciência (IGC), Portugal, where she remains as the Coordinator of the Science for Society Initiative and as the Director of the Graduate Program Science for Development (PGCD), aiming at improving science in Africa.
Her current research uses data analytics and machine learning to study complex problems at the interface between Biomedicine, Computation, Policy, Social Sciences, and Mathematics. These include epidemiology, critical thinking, network dynamics, political discourse, and their applications to human-behavior, with a large ethical and societal focus. She is also the President of the General Assembly of the Citizens Forum, an NGO that aims at improving the quality of the democratic discussion, through citizen assemblies.
Joana has a degree in Physics Engineering from Instituto Superior Técnico – University of Lisbon, and a PhD in Systems Biology from NOVA – ITQB, having developed her thesis at Harvard University, USA. In 2019, she was the recipient of an ERC Starting Grant to study human behavior using the online spread of “fake news” as a model system.
