Publication: Longitudinal modularity, a modularity for link streams
Longitudinal modularity, a modularity for link streams
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Brabant, V., Asgari, Y., Borgnat, P., Bonifati, A., & Cazabet, R. (2025). Longitudinal modularity, a modularity for link streams. EPJ Data Science, 14(1), 12. https://doi.org/10.1140/epjds/s13688-025-00529-x
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Temporal networks are commonly used to model real-life phenomena. When these phenomena represent interactions and are captured at a fine-grained temporal resolution, they are modeled as link streams. Community detection is an essential network analysis task. Although many methods exist for static networks, and some methods have been developed for temporal networks represented as sequences of snapshots, few works can handle directly link streams. This article introduces the first adaptation of the well-known Modularity quality function
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Brabant, V., Asgari, Y., Borgnat, P., Bonifati, A., & Cazabet, R. (2025). Longitudinal modularity, a modularity for link streams. EPJ Data Science, 14(1), 12. https://doi.org/10.1140/epjds/s13688-025-00529-x