I am an interdisciplinary scientist by training, having received my M.Sc. in Artificial Intelligence from the University of Edinburgh and a joint Ph.D. in Artificial Intelligence and Communication Science from the VU Amsterdam. In the decade since being awarded a VENI grant on mediatized agenda setting, I have grown into a leading computational communication scientist, developing and using state of the art computational communication science techniques. Combining these computational techniques with traditional panel survey methods allows studying the effect of individual media diets, for example in the recent Dutch parliamentary elections.
I am co-Director of The Societal Analytics Lab at the Vrije Universiteit Amsterdam. I have also co-founded and chaired the Computational Methods division in our international scientific association ICA, and I founded and am editor-in-chief of a new open access journal Computational Communication Research published by Amsterdam University Press and sponsored by multiple international universities.
prof. dr. Wouter van Atteveldt
Personal information
Research
My main research agenda is developing and applying the computational methods and tools needed to study media effects in a fragmented digital media landscape. As people consume news from an increasing number of traditional and social media sources, the field urgently needs to develop better ways to measure news consumption in order to study the effects of each person’s individual media diet. My research directly contributes to this development by furthering our pioneering work on data donation, where (fully informed and consenting) respondents donate a cleaned and minimized version of their social, mobile and digital news browsing history.
A second key methodological part of my research agenda is the introduction, adaptation and validation of methods from AI and computational linguistics into communication science research. Recent years have seen enormous gains in the development of attention models in deep learning, but these are only very slowly being used in the social sciences
A second key methodological part of my research agenda is the introduction, adaptation and validation of methods from AI and computational linguistics into communication science research. Recent years have seen enormous gains in the development of attention models in deep learning, but these are only very slowly being used in the social sciences
Ancillary activities
- Stichting Computational Communication Research | Amsterdam | Bestuurder | 2021-11-01 - present
Ancillary activities are updated daily
Publicaties
Persoonlijke website