activity
20212024
most citedA Bayesian semi-parametric approach for modeling memory decay in dynamic social networks

12 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SI2024

Simulating Relational Event Histories: Why and How

Rumana Lakdawala, Joris Mulder, Roger Leenders

Many important social phenomena are characterized by repeated interactions among individuals over time such as email exchanges in an organization or face-to-face interactions in a…

physics.flu-dyn2023

Capillary adhesion of stick insects

Guillermo J. Amador, Brett Klaassen van Oorschot, Uddalok Sen +2

Scientific progress within the last few decades has revealed the functional morphology of an insect's sticky footpads -- a soft, sponge-like pad that secretes a thin liquid film. H…

stat.ME2022★ 3 cited

A Bayesian actor-oriented multilevel relational event model with hypothesis testing procedures

Fabio Vieira, Roger Leenders, Daniel McFarland +1

Relational event network data are becoming increasingly available. Consequently, statistical models for such data have also surfaced. These models mainly focus on the analysis of s…

stat.ME2022★ 1 cited

Separating the Wheat from the Chaff: Bayesian Regularization in Dynamic Social Networks

Diana Karimova, Joris Mulder, Roger Th. A. J. Leenders

In recent years there has been an increasing interest in the use of relational event models for dynamic social network analysis. The basis of these models is the concept of an "eve…

stat.ME2021★ 12 cited

A Bayesian semi-parametric approach for modeling memory decay in dynamic social networks

Giuseppe Arena, Joris Mulder, Roger Th. A. J. Leenders

In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the quantity…