Capturing the social fabric: Population-scale socio-economic segregation patterns
Lecture by Yuliia Kazmina, Eszter Bokànyi, Eelke Heemskerk and Frank Takes at the 6th European Conference on Social Networks (EUSN 2022).
Anonymity of multi-hop neighborhoods in social networks
Lecture by Rachel de Jong, Frank Takes and Mark van der Loo at the 6th European Conference on Social Networks (EUSN 2022).
The anatomy of a population-scale social network
Lecture by Eszter Bokànyi, Eelke Heemskerk, Yuliia Kazmina and Frank Takes at the 6th European Conference on Social Networks (EUSN 2022).
Capturing socio-economic bubbles
Lightning talk by Yuliia Kazmina at Women in Network Science & Diversify NetSci joint satellite
Capturing the social fabric: population-scale socio-economic segregation patterns
Conference poster presentation by Yuliia Kazmina at Harper Center of the Booth School of Business at the University of Chicago.
Anonymity of Multi-hop Neighborhoods in Social Networks
Conference poster presentation by Rachel de Jong at Harper Center of the Booth School of Business at the University of Chicago.
The anatomy of a population-scale social network
Conference poster presentation by Eszter Bokányi at IC2S2 at the Harper Center of the Booth School of Business at the University of Chicago.
POPNET Connects with Floris Vermeulen
What do big data analytics reveal about neighbourhood organisational vitality?
Population-scale Social Network Analysis
Lecture by Frank Takes for the Interaction Data Lab of the Center for Research and Interdisciplinarity (CRI) in Paris.
Hackathon about anonymity in data was a great success
How anonymous is an individual in a social network dataset? That was the main subject of the hackathon organized by POPNET and Statistics Netherlands (CBS) on May 3 at Leiden University. By looking at openly available data on the internet, students had to derive the social network of several volunteers. The results give insight into what network data can be derived from public data, and therefore to what extent people in networks are really anonymous.