Get to know our research
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We study human behavior through digital traces with methods from complexity science, as part of the interdisciplinary field of Computational Social Science.
Some of our research lines are the following:Computational Affective Science
We combine big social data and computational modeling to understand affective life and emotional well-being.
Example publications:
Collective Emotions and Social Resilience in the Digital Traces After a Terrorist Attack. Psychological Science
The Dynamics of Emotions in Online Interaction. Royal Society Open Science
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Complex Privacy
We analyze online social networks discover how the actions of others affect the control we have on our data.
Example publications:
Leaking Privacy and Shadow Profiles in Online Social Networks. Science Advances
Collective aspects of privacy in the Twitter social network. EPJ Data Science
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Online Inequality
We study how online media capture and create inequalities in society at large.
Example publications:
Analyzing gender inequality through large-scale Facebook advertising data. PNAS
Quantifying the Economic and Cultural Biases of Social Media through Trending Topics. PLoS ONE
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Polarization Dynamics
We analyze the origins and consequences of opinion polarization and social fragmentation.
Example publications:
Ideological and Temporal Components of Network Polarization in Online Political Participatory Media. Policy & Internet
Social Signals and Algorithmic Trading of Bitcoin. Royal Society Open Science