#Social Networks #Dunbar number

¿Cuánta gente vas a acabar conociendo en toda tu vida?

Article (in Spanish) in the spanish newspaper El País about how many people we will know in our life. This is a summary of our recent research on how humans create/destroy relationships and how narrow and small is our world even throughout a life of encounters, relationships, work, etc. ¿Cuánta gente vas a acabar conociendo en toda tu vida? Muy poca En el mundo hay más de 7.500 millones de personas. ...

#Artificial Intelligence #Labour Markets

Towards understanding the impact of artificial intelligence on labor

title: ‘How to Organize your Deep Reinforcement Learning Agents: The Importance of Communication Topology’ author: Esteban Moro date: ‘2018-12-14’ categories: Publications tags: Deep Learning Networks image: /img/posts/NetES.jpg Authors: Frank, Morgan R and Autor, David and Bessen, James E and Brynjolfsson, Erik and Cebrian, Manuel and Deming, David J and Feldman, Maryann and Groh, Matthew and Lobo, José and Moro, Esteban and Wang, Dashun and Youn, Hyejin and Rahwan, Iyad ...

#Segregation #visualization #Urban Science #inequality

The Atlas of Inequality

Segregation is hurting our societies and specially our cities. But economic inequality isn’t just limited to neighborhoods. The restaurants, stores, and other places we visit in cities are all unequal in their own way. The Atlas of Inequality shows the income inequality of people who visit different places in the Boston metro area. It uses aggregated anonymous location data from digital devices to estimate people’s incomes and where they spend their time. ...

#social networks #Human Dynamics #Big Data

The dynamic character of our networked society

We live in a networked society and our actions, opinions, behaviors are affected and can affect other people. Understanding such social networked structures is one of the key challenges in our attempt to decode human behavior and its impact in our society. Although human interactions are dynamical by nature, most of our understanding relies in static representations of those social networks. However, social interactions are rarely static. Very often the networks evolve by means of processes that happen at diverse time scales, like link decay/formation, group formation, etc. ...