4 papers
Scalable dynamic community detection on temporal graphs using graph neural networks
Peijie Zhong, Raul Mondragon, Richard G. Clegg
Dynamic community detection on temporal graphs seeks to identify evolving community structures while allowing node memberships to change over time. In this work, we formulate dynam…
A model for generating temporal networks with dynamic community structure guided by mutual information
Peijie Zhong, Raúl Mondragón, Richard Clegg
This paper introduces a generative model for temporal networks that jointly controls community evolution and dynamic node sets. The model represents community structure as a sequen…
Mining a Decade of Event Impacts on Contributor Dynamics in Ethereum: A Longitudinal Study
Matteo Vaccargiu, Sabrina Aufiero, Cheick Ba +6
We analyze developer activity across 10 major Ethereum repositories (totaling 129884 commits, 40550 issues) spanning 10 years to examine how events such as technical upgrades, mark…
Quantifying community evolution in temporal networks
Peijie Zhong, Cheick Ba, Raúl Mondragón +1
When we detect communities in temporal networks it is important to ask questions about how they change in time. Normalised Mutual Information (NMI) has been used to measure the sim…