research-article

Dynamic Structural Role Node Embedding for User Modeling in Evolving Networks

Authors:

Chenghan Huang,

Soroush VosoughiAuthors Info & Claims

ACM Transactions on Information Systems (TOIS), Volume 40, Issue 3

Article No.: 46, Pages 1 - 21

https://doi.org/10.1145/3472955

Published: 22 November 2021 Publication History

Abstract

Complex user behavior, especially in settings such as social media, can be organized as time-evolving networks. Through network embedding, we can extract general-purpose vector representations of these dynamic networks which allow us to analyze them without extensive feature engineering. Prior work has shown how to generate network embeddings while preserving the structural role proximity of nodes. These methods, however, cannot capture the temporal evolution of the structural identity of the nodes in dynamic networks. Other works, on the other hand, have focused on learning microscopic dynamic embeddings. Though these methods can learn node representations over dynamic networks, these representations capture the local context of nodes and do not learn the structural roles of nodes. In this article, we propose a novel method for learning structural node embeddings in discrete-time dynamic networks. Our method, called HR2vec, tracks historical topology information in dynamic networks to learn dynamic structural role embeddings. Through experiments on synthetic and real-world temporal datasets, we show that our method outperforms other well-known methods in tasks where structural equivalence and historical information both play important roles. HR2vec can be used to model dynamic user behavior in any networked setting where users can be represented as nodes. Additionally, we propose a novel method (called network fingerprinting) that uses HR2vec embeddings for modeling whole (or partial) time-evolving networks. We showcase our network fingerprinting method on synthetic and real-world networks. Specifically, we demonstrate how our method can be used for detecting foreign-backed information operations on Twitter.

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Cited By

Yu XLv LLing C(2024)Dynamic Evolution Modeling and Computer Simulation Analysis in Complex Networks2024 International Conference on Telecommunications and Power Electronics (TELEPE)10.1109/TELEPE64216.2024.00129(688-693)Online publication date: 29-May-2024
https://doi.org/10.1109/TELEPE64216.2024.00129
Meng CAliannejadi Mde Rijke MFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)System Initiative Prediction for Multi-turn Conversational Information SeekingProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3615070(1807-1817)Online publication date: 21-Oct-2023
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Somanchi SAbbasi AKelley KDobolyi DYuan T(2023)Examining User Heterogeneity in Digital ExperimentsACM Transactions on Information Systems10.1145/357893141:4(1-34)Online publication date: 22-Mar-2023
https://dl.acm.org/doi/10.1145/3578931
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Index Terms

Dynamic Structural Role Node Embedding for User Modeling in Evolving Networks
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Learning latent representations
2. Networks
  1. Network properties
    1. Network structure
      1. Topology analysis and generation

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Published In

cover image ACM Transactions on Information Systems

ACM Transactions on Information Systems Volume 40, Issue 3

July 2022

650 pages

ISSN:1046-8188

EISSN:1558-2868

DOI:10.1145/3498357

Editor:
Min Zhang
Tsinghua University, China

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 22 November 2021

Accepted: 01 June 2021

Revised: 01 April 2021

Received: 01 October 2020

Published in TOIS Volume 40, Issue 3

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Cited By

Yu XLv LLing C(2024)Dynamic Evolution Modeling and Computer Simulation Analysis in Complex Networks2024 International Conference on Telecommunications and Power Electronics (TELEPE)10.1109/TELEPE64216.2024.00129(688-693)Online publication date: 29-May-2024
https://doi.org/10.1109/TELEPE64216.2024.00129
Meng CAliannejadi Mde Rijke MFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)System Initiative Prediction for Multi-turn Conversational Information SeekingProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3615070(1807-1817)Online publication date: 21-Oct-2023
https://dl.acm.org/doi/10.1145/3583780.3615070
Somanchi SAbbasi AKelley KDobolyi DYuan T(2023)Examining User Heterogeneity in Digital ExperimentsACM Transactions on Information Systems10.1145/357893141:4(1-34)Online publication date: 22-Mar-2023
https://dl.acm.org/doi/10.1145/3578931
Wang LHuang CCao XMa WVosoughi S(2023)Graph-Level Embedding for Time-Evolving GraphsCompanion Proceedings of the ACM Web Conference 202310.1145/3543873.3587299(5-8)Online publication date: 30-Apr-2023
https://doi.org/10.1145/3543873.3587299
Qin MZhang CBai BZhang GYeung D(2023)High-Quality Temporal Link Prediction for Weighted Dynamic Graphs via Inductive Embedding AggregationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.323836035:9(9378-9393)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1109/TKDE.2023.3238360
Vicentiy A(2023)Intelligent Decision Support Based on Mental User Models: Research DesignSoftware Engineering Application in Systems Design10.1007/978-3-031-21435-6_63(732-740)Online publication date: 1-Jan-2023
https://doi.org/10.1007/978-3-031-21435-6_63
Yang MZhou MXiong HKing I(2022)Hyperbolic Temporal Network EmbeddingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.323239835:11(11489-11502)Online publication date: 27-Dec-2022
https://dl.acm.org/doi/10.1109/TKDE.2022.3232398
Pan TWang WShao MSun YJiao P(2022)Role-Oriented Dynamic Network Embedding2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020276(1070-1079)Online publication date: 17-Dec-2022
https://doi.org/10.1109/BigData55660.2022.10020276

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