Computational Social Sciences / Temporal Network Theory

Modeling frameworks and tools.- 24 ways of thinking about your temporal network data.- Density and related concepts for discrete, directed, and/or weighted stream graphs.- Dynamics and control of stochastically switching networks: Beyond fast switching.- Visualisation of structure and processes on temporal networks.- Mapping sequences of events in temporal networks onto weighted event graphs.- Measures of temporal network structure.- Eigenvector-based centralities for temporal networks: Supracentralities with directed interlayer coupling.- Temporal graph metrics for temporal text networks.- Characterization of correlated bursts for temporal networks.- Mesoscopic structures.- Challenges in community discovery on temporal networks.- Fundamental structures in dynamic social networks.- Mapping and modelling sequences and temporal networks with dynamic community structures.- Epidemic spreading.- Spreading of infection on temporal networks: an edge-centered perspective.- The effect of concurrency on epidemic threshold in time-varying networks.- Epidemic thresholds on continuous-time evolving networks.- Other dynamic processes.- Reachability and concurrency in temporal networks.- The effects of local and global links creation mechanisms on spreading processes.- Information diffusion backbones.- Influence maximization in temporal networks.- Random walks on temporal networks.

Petter Holme is a specially appointed professor at Tokyo Institute of Technology. His research interests cover many aspects of network science-from data science to theory. He has about 150 scientific publications including about 30 on temporal networks.