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Temporal distance metrics for social network analysis

Authors:

Mirco Musolesi,

Cecilia Mascolo,

Vito LatoraAuthors Info & Claims

WOSN '09: Proceedings of the 2nd ACM workshop on Online social networks

Pages 31 - 36

https://doi.org/10.1145/1592665.1592674

Published: 17 August 2009 Publication History

Abstract

The analysis of social and technological networks has attracted a lot of attention as social networking applications and mobile sensing devices have given us a wealth of real data. Classic studies looked at analysing static or aggregated networks, i.e., networks that do not change over time or built as the results of aggregation of information over a certain period of time. Given the soaring collections of measurements related to very large, real network traces, researchers are quickly starting to realise that connections are inherently varying over time and exhibit more dimensionality than static analysis can capture.

In this paper we propose new temporal distance metrics to quantify and compare the speed (delay) of information diffusion processes taking into account the evolution of a network from a local and global view. We show how these metrics are able to capture the temporal characteristics of time-varying graphs, such as delay, duration and time order of contacts (interactions), compared to the metrics used in the past on static graphs. As a proof of concept we apply these techniques to two classes of time-varying networks, namely connectivity of mobile devices and e-mail exchanges.

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Cited By

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https://doi.org/10.12677/ORF.2024.141055
Gionis AOettershagen LSarpe IChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Mining Temporal NetworksCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3641245(1260-1263)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3641245
Li YZhao YXu TWu S(2024)Node Importance Research of Temporal CPPS Networks for Information FusionIEEE Transactions on Reliability10.1109/TR.2023.332912473:2(1291-1301)Online publication date: Jun-2024
https://doi.org/10.1109/TR.2023.3329124
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Index Terms

Temporal distance metrics for social network analysis
1. Hardware
  1. Communication hardware, interfaces and storage
2. Networks
  1. Network properties
    1. Network structure

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Published In

cover image ACM Conferences

WOSN '09: Proceedings of the 2nd ACM workshop on Online social networks

August 2009

74 pages

ISBN:9781605584454

DOI:10.1145/1592665

Program Chairs:
Jon Crowcroft
University of Cambridge
,
Balachander Krishnamurthy
AT&T Labs -- Research

Copyright © 2009 ACM.

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 ACM 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: 17 August 2009

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SIGCOMM '09

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SIGCOMM '09: ACM SIGCOMM 2009 Conference

August 17, 2009

Barcelona, Spain

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Overall Acceptance Rate 12 of 36 submissions, 33%

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Cited By

李智(2024)Node Importance Identification Algorithm for Temporal Networks Based on Node SimilarityOperations Research and Fuzziology10.12677/ORF.2024.14105514:01(590-598)Online publication date: 2024
https://doi.org/10.12677/ORF.2024.141055
Gionis AOettershagen LSarpe IChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Mining Temporal NetworksCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3641245(1260-1263)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3641245
Li YZhao YXu TWu S(2024)Node Importance Research of Temporal CPPS Networks for Information FusionIEEE Transactions on Reliability10.1109/TR.2023.332912473:2(1291-1301)Online publication date: Jun-2024
https://doi.org/10.1109/TR.2023.3329124
Tan TCao XSong FChen SDu WLi Y(2024)Temporal Link Prediction via Auxiliary Graph TransformerIEEE Transactions on Network Science and Engineering10.1109/TNSE.2024.348509311:6(5954-5968)Online publication date: Nov-2024
https://doi.org/10.1109/TNSE.2024.3485093
Lu HLi YMa K(2024)EHRFlow: A Visual Analytics Approach to Studying Healthcare Professionals' Communication Effectiveness and Efficiency2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)10.1109/CHASE60773.2024.00021(120-131)Online publication date: 19-Jun-2024
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Jerônimo CPatrocínio ZMalinowski SGuimarães SGravier G(2023)A Novel Method for Temporal Graph Classification based on Transitive Reduction2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA60987.2023.10302525(1-10)Online publication date: 9-Oct-2023
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Yu JXiao BCui Y(2023)A Review of Temporal Network Analysis and Applications3D Imaging—Multidimensional Signal Processing and Deep Learning10.1007/978-981-99-1230-8_1(1-10)Online publication date: 3-May-2023
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Zou RLiu YZang QWei BLiu CHou JZhou YChe J(2022)Research and Development of Cyber Cyberspace Resilience Technology2022 International Conference on Information Technology, Communication Ecosystem and Management (ITCEM)10.1109/ITCEM57303.2022.00014(23-28)Online publication date: Dec-2022
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