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A science of digital societies
C3-UNAM, Mexico


The last centuries have witnessed a great surge in our understanding and control of ‘simple’ physical, chemical, and biological processes through data analysis and the mathematical modelling of their underlying dynamics. Encouraged by this success, researchers have recently tried to do the same for social, ecological, and economic systems, thanks to the massive data generated by information-communication technologies and the unprecedented fusion of off- and online human activity. However, due to the presence of adaptability, feedback loops, and strong heterogeneities in the elements and interactions comprising our modern digital societies, it is unclear if statistical ‘laws’ of socio-technical behaviour even exist, akin to those found for natural processes. This continuing search has resulted in the fields of network science and computational social science, which share the goal of modelling social phenomena with enough accuracy to make reliable predictions. In this talk I summarise some of my earlier and ongoing contributions to these fields, dealing with social influence in the spreading of Skype and other social networks, the evolution of social conflicts in collaborative platforms like Wikipedia, and the persistent temporal features of hierarchies in socio-technical systems. I also discuss possibilities to continue this research, such as more realistic models of social dynamics, the use of statistical inference and machine learning techniques to compare idealised models, and the creation of loops between data acquisition and model analysis to increase prediction accuracy. All of this with the goal of contributing to a ‘science of digital societies’, which will be able to provide quantitative tools to better understand the complex societies of our day

A quick intro to Python and its advantages for academic research
CIDE, Mexico

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DNDS, CEU, Budapest