Temporal network compression via network hashing

Vaudaine, R. and Borgnat, P. and Gonçalves, P. and Gribonval, R. and Karsai, Márton (2024) Temporal network compression via network hashing. APPLIED NETWORK SCIENCE, 9 (1). ISSN 2364-8228

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Pairwise temporal interactions between entities can be represented as temporal networks, which code the propagation of processes such as epidemic spreading or information cascades, evolving on top of them. The largest outcome of these processes is directly linked to the structure of the underlying network. Indeed, a node of a network at a given time cannot affect more nodes in the future than it can reach via time-respecting paths. This set of nodes reachable from a source defines an out-component, which identification is costly. In this paper, we propose an efficient matrix algorithm to tackle this issue and show that it outperforms other state-of-the-art methods. Secondly, we propose a hashing framework to coarsen large temporal networks into smaller proxies on which out-components are more easily estimated, and then recombined to obtain the initial components. Our graph hashing solution has implications in privacy respecting representation of temporal networks. © 2024, The Author(s).

Item Type: Article
Uncontrolled Keywords: State-of-the-art methods; Underlying networks; temporal networks; temporal networks; Epidemic spreading; Information cascades; Network compression; Matrix algorithms; Graph hashing; Graph hashing; Out-component calculation; Out-component calculation; Streaming matrix algorithms; Streaming matrix algorithm;
Subjects: Q Science / természettudomány > QA Mathematics / matematika
Q Science / természettudomány > QA Mathematics / matematika > QA76.527 Network technologies / Internetworking / hálózati technológiák, hálózatosodás
Depositing User: MTMT SWORD
Date Deposited: 28 Mar 2024 09:43
Last Modified: 28 Mar 2024 09:43

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