Johan Koskinen

Analysing networks of networks

Johan Koskinen, Pete Jones, Darkhan Medeuov, Artem Antonyuk, Kseniia Puzyreva, Nikita Basov

Journal article  |  2023  |  Social Networks

Multilevel longitudinal analysis of social networks

Johan Koskinen, Tom AB Snijders

Journal article  |  2023  |  Journal of the Royal Statistical Society Series A: Statistics in Society

Abstract Stochastic actor-oriented models (SAOMs) are a modelling framework for analysing network dynamics using ne..

Multilevel network interventions: Goals, actions, and outcomes

Garry Robins, Dean Lusher, Chiara Broccatelli, David Bright, Colin Gallagher, Maedeh Aboutalebi Karkavandi, Petr Matous, James Coutinho, Peng Wang, Johan Koskinen, Bopha Roden, Giovanni Radhitio Putra Sadewo

Journal article  |  2023  |  SOCIAL NETWORKS

COVID-19 has resulted in dramatic and widespread social network interventions across the globe, with public health measures such a..

Information Retrieval and Survey Design for Two-Stage Customer Preference Modeling

Y Xiao, Y Cui, N Raut, JH Januar, J Koskinen, N Contractor, W Chen, Z Sha

Conference Proceedings  |  2022  |  Proceedings of the Design Society

Customer survey data is critical to supporting customer preference modeling in engineering design. We present a framework of infor..

Reprint of: Trust, quality, and the network collection experience: A tale of two studies on the Democratic Republic of the Congo

P Stys, S Muhindo, S N'simire, I Tchumisi, P Muzuri, B Balume, J Koskinen

Journal article  |  2022  |  Social Networks

Data collection in social network research has advanced to include online questionnaires, digital metadata mining of internet site..

Bayesian analysis of social influence

Johan Koskinen, Galina Daraganova

Journal article  |  2022  |  JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY

The network influence model is a model for binary outcome variables that accounts for dependencies between outcomes for units that..

Circular specifications and predicting with information from the future: Errors in the empirical SAOM-TERGM comparison of Leifeld & Cranmer

P Block, J Hollway, C Stadtfeld, J Koskinen, T Snijders

Journal article  |  2022  |  Network Science

We review the empirical comparison of Stochastic Actor-oriented Models (SAOMs) and Temporal Exponential Random Graph Models (TERGM..

Trust, quality, and the network collection experience: A tale of two studies on the Democratic Republic of the Congo

P Stys, S Muhindo, S N'simire, I Tchumisi, P Muzuri, B Balume, J Koskinen

Journal article  |  2022  |  Social Networks

Data collection in social network research has advanced to include online questionnaires, digital metadata mining of internet site..

Network formation in organizational settings: Exploring the importance of local social processes and team-level contextual variables in small groups using bayesian hierarchical ERGMs

F Agneessens, FJ Trincado-Munoz, J Koskinen

Journal article  |  2022  |  Social Networks

Statistical models for social networks, such as exponential random graphs (ERGMs), have increasingly been used by organizational s..

Exponential Random Graph Modelling

Johan Koskinen

Book Chapter  |  2021