Personal tools
You are here: Home / News and events / Event items / New data and methods for migration studies: going beyond traditional data sources

New data and methods for migration studies: going beyond traditional data sources

When 10 Oct 2022 09:00 AM to
11 Oct 2022 06:00 PM
Where Paris School of Economics and Institut Convergences Migrations
Contact Name
Add event to calendar vCal

The Paris School of Economics, SoBigData++ consortium, HumMingBird consortium and Institut Convergences Migrations jointly organised a two-day workshop aimed at bringing together migration scholars from various disciplines from these institutions and beyond. The conference was devoted to investigating and showcasing new methods to study human migration based on non-traditional data sources and methods.

Possible topics included:

  • understanding and estimating migration flows and stocks using non-traditional and big data sources (e.g. nowcasting flows using social media or mobile phone data, visualisation, analysis, and prediction of flows, including for specific domains such as scientific, labour, refugee, and seasonal migration);
  • studying the connection between policy changes and migration using new data analytics; understanding attitudes towards migrants and migrants’ integration (e.g. using sentiment analysis, discourse type and media portraying of migrants, polarisation of the discourse with respect to human migration, etc.);
  • ethics of big data in the context of human migration.

Organising and scientific committee

Hillel Rapoport (Paris School of Economics), Tuba Bircan (Vrije Universiteit Brussel), Alina Sirbu (University of Pisa), and Jerome Valette (University Paris 1 Pantheon-Sorbonne), Donia Kamel (Paris School of Economics).

Keynote speakers

Prof. Joshua Blumenstock
Dr. Joshua Blumenstock is a Chancellor’s Associate Professor at the UC Berkeley School of Information and the Goldman School of Public Policy. He is the Co-director of the Global Policy Lab and the Center for Effective Global Action. Blumenstock does research at the intersection of machine learning and empirical economics, and focuses on using novel data and methods to understand the causes and consequences of global poverty, and to improve the lives of disadvantaged people around the world. He has a PhD in Information Science and a MA in Economics from UC Berkeley, and Bachelor’s degrees in Computer Science and Physics from Wesleyan University. He is a recipient of awards including the NSF CAREER award, the Intel Faculty Early Career Honor, and the UC Berkeley Chancellor's Award for Public Service. His work has appeared in general interest journals including Science, Nature, and Proceedings of the National Academy of Sciences, as well as top economics journals (e.g., the American Economic Review) and computer science conferences (e.g., ICML, KDD, AAAI, WWW, CHI).

Prof. Katia Zhuravskaya
Prof. is Professor of Economics at the Paris School of Economics and EHESS and the Director of Studies at School for Advanced Studies in the Social Sciences. Her research focuses on empirical political economics and the economics of the media. In recent years, she has studied factors that make ethnic diversity important for conflict and economic development, including the impact of forced mass movements of ethnic groups in Eastern Europe and from Eastern Europe to Central Asia during WWII, the impact of ethnic occupational segregation on ethnic tensions in the context of historical anti-Jewish violence in Europe, and the impact of political manipulation on ethnic conflict in Central Asia. She has also published research in an array of different microeconomic and macroeconomic disciplines. Here is a short list from her CV: Fiscal Federalism, arbitrage in the stock market, tax arrears in Russia concerning liquidity and federal redistribution, entrepreneurs in Russia, religions in Russia, Chinese entrepreneurs, bias in Russian commercial courts, decentralisation and political institutions, revision to privatisation in socialist regimes, the media and political persuasion, forced migration, and the effects of social media on politics.

Dr. Petra Molnar
Petra Molnar is a lawyer and researcher specialising in technology, migration, and human rights. She is currently working with EDRi, Homo Digitalis, and other partner organisations on a project looking at the impacts of migration control technologies on the lives of people on the move, funded by the Mozilla and Ford Foundations. Petra also works on issues around immigration detention, health and human rights, gender-based violence, and the politics of refugee, immigration, and international law. Her work has appeared in numerous academic publications and the popular press, including the New York Times. Petra is also the co-author of ‘Bots at the Gate’, an internationally recognised report on the human rights impacts of automated decision-making in immigration and refugee systems. She holds a Master of Arts in Anthropology from York University, a Juris Doctorate from the University of Toronto, and an LL.M in International Law from the University of Cambridge.

Dr. Stefano Maria Iacus
Stefano Maria Iacus is a senior research scientist and the director of Data Science and Product Research at the Institute for Quantitative Social Science (IQSS), Harvard University. He received his bachelor’s degree in statistics, magna cum laude, in 1995 at the Sapienza University of Rome (Italy). He completed his PhD in statistics at the University of Padua (Italy) in 1998, and his PhD in mathematics in 1999 at the Le Mans University (France). He was a member of the R Core Team (1999-2014) for the development of the R statistical environment and now is a member of the R Foundation. His research interests include inference for stochastic processes, simulation, quantitative finance, computational statistics, causal inference, text mining, and sentiment analysis. 


Tuba Bircan