Temporal Motif Participation Profiles for Analyzing Node Similarity in Temporal Networks

Fuente: arXiv
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Main Authors: Lee, Maxwell C., Xu, Kevin S.
Format: Preprint
Published: 2025
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author Lee, Maxwell C.
Xu, Kevin S.
author_facet Lee, Maxwell C.
Xu, Kevin S.
contents Temporal networks consisting of timestamped interactions between a set of nodes provide a useful representation for analyzing complex networked systems that evolve over time. Beyond pairwise interactions between nodes, temporal motifs capture patterns of higher-order interactions such as directed triangles over short time periods. We propose temporal motif participation profiles (TMPPs) to capture the behavior of nodes in temporal motifs. Two nodes with similar TMPPs take similar positions within temporal motifs, possibly with different nodes. TMPPs serve as unsupervised embeddings for nodes in temporal networks that are directly interpretable, as each entry denotes the frequency at which a node participates in a particular position in a specific temporal motif. We demonstrate that clustering TMPPs reveals groups of nodes with similar roles in a temporal network through simulation experiments and a case study on a network of militarized interstate disputes.
format Preprint
id arxiv_https___arxiv_org_abs_2507_06465
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Temporal Motif Participation Profiles for Analyzing Node Similarity in Temporal Networks
Lee, Maxwell C.
Xu, Kevin S.
Social and Information Networks
Physics and Society
Temporal networks consisting of timestamped interactions between a set of nodes provide a useful representation for analyzing complex networked systems that evolve over time. Beyond pairwise interactions between nodes, temporal motifs capture patterns of higher-order interactions such as directed triangles over short time periods. We propose temporal motif participation profiles (TMPPs) to capture the behavior of nodes in temporal motifs. Two nodes with similar TMPPs take similar positions within temporal motifs, possibly with different nodes. TMPPs serve as unsupervised embeddings for nodes in temporal networks that are directly interpretable, as each entry denotes the frequency at which a node participates in a particular position in a specific temporal motif. We demonstrate that clustering TMPPs reveals groups of nodes with similar roles in a temporal network through simulation experiments and a case study on a network of militarized interstate disputes.
title Temporal Motif Participation Profiles for Analyzing Node Similarity in Temporal Networks
topic Social and Information Networks
Physics and Society
url https://arxiv.org/abs/2507.06465