Understanding Our Complex World Using Data Analytics and Models

Satellite session-Conference on Complex Systems 2017
September 20, Room 9





Yaneer Bar-Yam

The complexity of global systems


Tarik Roukny

The Price of Complexity in Financial Networks and Compressing Networked Markets


Alessandro Pluchino, Alessio Emanuele Biondo and Andrea Rapisarda

Informative Contagion Dynamics in a Multilayer Network Model of Financial Markets


Florentino Borondo

Markets in Complex Networks


Hiroki Sayama

Mechanistic modeling of social systems


Coffe break


Cesar Hidalgo

Collective learning in society and the economy


Bonnie Johnson

Engineering Complex Systems Using Automated Decision Aids


Myriam Patricia Cifuentes, Clara Mercedes Suarez and Ricardo A. Cifuentes

Under the waterline of the iceberg: network analysis uncovers factors that moderate stillbirth attributed to Zika Virus Infection


Kenneth Acquah and Arnaud Grignard

A New Perspective Toward the Design of Creative Cities


Dan Calacci, Esteban Moro and Alex Pentland

Exploring urban inter-group social contact using high resolution geospatial data


Yuan Yuan, Ahmad Alabdulkareem and Alex Pentland

Social Network Formation Based on Endowment Exchange and Social Representation


Cristian Jara Figueroa, Jian Gao, Bogang Jun and Cesar Hidalgo

Where do new industries come from? The importance of related knowledge


Wrap up, discussion, make up time for questions


The goal of this satellite meeting is to present advances in the analysis of social, economic and political challenges, using big data and modeling, such as data for policy making, markets dynamics, economic growth and crises, unemployment, social inequality, ethnic violence, social unrest, immigration, political polarization, predictability of elections, global risks, extreme events, privacy, hidden interdependencies, unintended consequences, etc. We expect to raise awareness about interventions in complex systems, the risk we face when societies become global, the opportunities that are created, and the role of complexity in data analytics.

New technologies are enabling social communication and coordination on unprecedented scales. The world is becoming more economically, politically and socially integrated and previously local issues are now becoming global. Counterintuitively, instead of homogenizing society, the excess of connections seems to be increasingly differentiating and fragmenting it. Recent electoral processes have shown that the Internet can increase polarization instead of reducing it and that the way globalization has been implemented is fraught with conflict and economic distress. These seemingly unrelated phenomena have similar causes: the complex dynamics of social systems and the non-linear effects of increasing inter-dependencies among complex systems’ parts.

Policy and decision makers are hardly able to understand or cope with the current world. They have failed to foresee ongoing social changes and have not been able to effectively respond to them. This is partly because of the unpredictable nature of complex systems, but mainly because of the limitations of available models and analytical tools. These are not adequate for understanding the complexity of social systems, especially in a global context.

The opportunities available from big data could solve this problem but we must analyze the data properly. The right framing of understanding and analytical toolsets could could enhance our understanding of social systems and enable the design of better technologies and intervention strategies. Ultimately, we could benefit from the complexity of social systems, rather than being endangered by it.

The goal of this satellite session is to manifest the behavior of social systems in the context of increasing communication and globalization and to show new ways to model social systems and treat big data in order to formulate the right questions and retrieve the relevant information. Our scope is to show the value of modeling and data analytics for understanding complex social systems and to explore new ways to analyze the data, taking into account the complexity of underlying systems. We expect to raise awareness about interventions in complex systems, the risk we face when societies become global, the opportunities that are created, and the role of complexity in data analytics.

The satellite will cover the following aspects:

  • Global economical and social systems
  • Global risks
  • Globalization
  • Political systems
  • Polarization
  • Social unrest
  • Data for policy making
  • Data for development
  • Ethics and privacy
  • Multi-scale analysis of social systems
  • Social networks analysis
  • Fat tailed distributions
  • Out of equilibrium economics
  • Adaptive network models
  • Agent based models
  • Non-linear social dynamics

Invited Speakers

Yaneer Bar-Yam, NECSI: The complexity of global systems.
Hiroki Sayama, Binghamton U.: Mechanistic modeling of social systems.
Cesar Hidalgo, MIT: Collective learning in society and the economy.


The satellite meeting will be hosted by Conference on Complex Systems 2017. The CCS’17 meeting will take place in Cancun, Mexico during Sept 17-22, 2017. CSS’17 is a major annual international event gathering diverse communities engaged in Complex Systems research, ranging from Life Sciences to Physics, from Computer Science to Social Sciences, and from Networks to Policy Implications.

All participants of the satellite meeting (with or without abstract submission) have to register to CCS '17.


Alfredo J. Morales
New England Complex Systems Institute
Massachusetts Institute of Technology

NECSI advances the development of complex systems science and its applications to real world problems, including social policy matters. We study how interactions within a system lead to its behavioral patterns and how the system interacts with its environment. Our researchers study data science, networks, agent-based modeling, multi-scale analysis and complexity

Alfredo contributes to building a better understanding of social systems by developing computational and analytical methods based on complex systems science and data science. His work is at the intersection of computer science, statistics, applied physics and artificial intelligence. He analyzes large datasets that result from human activity on social media, internet, mobile phones or purchases in order to retrieve unstructured patterns of collective behaviors that explain large scale societal properties, such as social dynamics, urban dynamics, segregation, political engagement, political polarization and social influence.

Rosa M. Benito
Technical University of Madrid

Rosa heads the Complex Systems Group at The Technical University of Madrid (UPM) and is also Professor of Applied Physics at UPM. Prof. Benito's work focuses on understanding and characterizing the structure and dynamics of different complex systems by using Complex Network Theory and Data Science. In particular she has proposed a new formalism to model complex networks topology, and she has been working with big data to determine the individual and collective behavior of users in specific online conversation on Twitter, and human mobility patterns through mobile phone data. She has lead many research projects and has participated in several Challenge for Development using mobile phone data from African's countries (Ivory Coast and Senegal). Her work has been published in many academic publications. She head the PhD Program in Complex Systems and has supervised several PhD Thesis. She has been awarded for Excellence in her Academic Career and for Innovation Education from UPM.

Program committee

Xiaowen Dong
MIT Media Lab

Juan Carlos Losada
Universidad Politecnica de Madrid



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