Ulf Aslak forsvarer sin ph.d.-afhandling

Ulf Aslak forsvarer sin ph.d.-afhandling:"Complexity in Social Data. Towards mapping and understanding complex phenomena in big social systems, using data science"

Kandidat

Ulf Aslak

Titel

"Complexity in Social Data. Towards mapping and understanding complex phenomena in big social systems, using data science".

Tid og sted

28. november 2019 kl. 14:00, Københavns Universitet, CSS, Øster Farimagsgade 5, 1353 København K, CSS 1.1.18. Af hensyn til kandidaten lukkes dørene præcis.

Bedømmelsesudvalg

Professor Mogens Fosgerau, Økonomisk Institut, Københavns Universitet, Danmark (formand
Specially appointed professor Petter Holme, Institute of Innovative Research, Tokyo Institute of Technology, Japan
Professor Francisco Camara Pereira, DTU

Abstract 

It is now possible to accurately measure human behavior and understand it at large scales. Smartphones, social media sites and markets deliver a massive stream of data, that can be tapped into to understand previously unknown social phenomena. One of the things we are discovering is that human social systems are highly complex, displaying many of the hallmarks of complex systems, such as large scale self-organization and reoccurring patterns. At the same time, they are extremely chaotic, making it near impossible to accurately simulate or predict their behavior. Computational social science, or social data science, has therefore emerged as an interdisciplinary field of social scientists turned data scientists and vice versa, with the ambition to answer fundamental questions about human behavior. Operating within this field, this thesis explores complex phenomena in social and behavioral data. It spans a wide range of topics within different fields, from neuroscience to animal ecology, but is connected throughout by the idea of complexity.

Det vil være muligt før forsvaret at rekvirere en kopi af afhandlingen ved henvendelse til Receptionen (26.0.20), Økonomisk Institut