Maxi San Miguel – Institute for Cross-Disciplinary Physics and Complex Systems (IFISC), Campus Universitat de les Illes Balears, Spain.
What can we learn from simple models of social interaction?
To convey the message that we need to understand the mechanisms that operate in complex systems to be able to understand data, I will address the following question: When and how collective agreement is reached by processes of social imitation?. I will review how the simple Voter Model, an implementation of social imitation, provides answers to this question depending on the topology of the network of interactions, activity patterns, random events, co-evolution dynamics, social multiplexing, etc. I will then show how a metapopulation Voter Model, with input data about geographic population distribution and population mobility, can explain and reproduce statistical regularities of the US presidential elections.
Marco Tomassini – Faculty of Business and Economics, Université de Lausanne, Switzerland.
Strategic interactions and network evolution. (slides)
The game theory approach has been one of the most successful in the social and economic sciences to describe how agents should behave in situations that imply interdependent decision making. When it comes to explain actual agents’ behavior, however, game theory models are not entirely convincing in many cases. In this talk we shall present the application of game theory to the fundamental problem of cooperation in human societies. After a quick review of standard game theory concepts, we shall describe its application to populations of agents that interact through networks of contacts that can evolve according to some exogenous process. We will then compare the predictions of models and simulations with a number of recent results obtained by performing experiments with humans in the laboratory under similar conditions. A discussion of the methodologies and of the scope of the results will conclude the presentation.
Sandro Meloni – Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Spain.
Use and misuse of data from Online Social Networks a. k. a. What you can’t do with Twitter in your papers (slides)
Facebook, Twitter and all the other online social networks offer an incredible opportunity to connect with our friends and share our life with them, but everything comes with a prize: our privacy. Every minute more than 350.000 tweets are sent and over 4 million Facebook posts are liked, generating in one day more data than those generated by all of human history till the year 2000. This unbelievable amount of information about our behaviour and habits represents the fortune of many private companies, but also an unprecedented opportunity for scientists in several fields, from social sciences to mobility and economics. The aim of this talk is to give an overview of the possibilities offered by the study of data from online social systems to scientists working in complex systems, but also of the long list of limitations that come with them. Along with the technical issues of getting and managing such huge amount of information, I will highlight the risks that could arise from the wrong interpretation of human behaviour in online contests, and the possible biases at the socio-demographic level. Finally, if time allows, I will also present some recent applications of data analysis to epidemiology and sociology.
Saúl Ares – Grupo Interdisciplinar de Sistemas Complejos, Universidad Carlos III de Madrid, Spain.
Science at the crossroads of physics and biology: embryonic development (slides).
The study of complex systems is all about the emergence of complexity out of simplicity. Here I will present a paradigmatic example in biology: the development of an embryo, where starting from a single cell all the intricately organized organs and tissues of an adult animal appear. I will review examples of how tools from complexity science such as statistical mechanics and nonlinear dynamics help to understand developmental processes, paying special attention to developmental pattern formation. A common feature of any successful study in the field is the integration of experimental and theoretical work.
Xavier Busquets Carretero – Department of Operations, Innovation and Data Sciences in ESADE and Fundacion Sicomoro
Discovering Paths: Exploring emergence and IT evolutionary design in cross-border M&A, the case of Santander acquiring Abbey (2004-2009)
Discovery paths in M&A are presented as an evolving process exploring the “variations” to generate expected and emergent synergies. Discovery paths are dependent on IT modular architectures and IT governance. The realisation of expected synergies is based on the generation of economies of scale and scope as well as economies of learning and increasing returns leverage of existing capabilities, but emergent synergies are dependent on modular design to cope with complex contingencies. He will argue that a discovery path has the function of endogenizing technology creating a new open platform that transforms the business model into a mulit-local banking system. He will illustrate these propositions in the IT transfer within the M&A between Santander and Abbey (2004-2009).