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Information diffusion in online social networks: a survey

Authors:

Djamel A. ZighedAuthors Info & Claims

ACM SIGMOD Record, Volume 42, Issue 2

Pages 17 - 28

https://doi.org/10.1145/2503792.2503797

Published: 16 July 2013 Publication History

Abstract

Online social networks play a major role in the spread of information at very large scale. A lot of effort have been made in order to understand this phenomenon, ranging from popular topic detection to information diffusion modeling, including influential spreaders identification. In this article, we present a survey of representative methods dealing with these issues and propose a taxonomy that summarizes the state-of-the-art. The objective is to provide a comprehensive analysis and guide of existing efforts around information diffusion in social networks. This survey is intended to help researchers in quickly understanding existing works and possible improvements to bring.

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Cited By

Brooks HPorter M(2025)An “opinion reproduction number” for infodemics in a bounded-confidence content-spreading process on networksChaos: An Interdisciplinary Journal of Nonlinear Science10.1063/5.020643135:1Online publication date: 30-Jan-2025
https://doi.org/10.1063/5.0206431
Singh SSrivastava DVerma MMuhuri S(2025)Information diffusion analysis: process, model, deployment, and applicationThe Knowledge Engineering Review10.1017/S026988892400010939Online publication date: 22-Jan-2025
https://doi.org/10.1017/S0269888924000109
Zhu EWang HZhang YMa M(2025)SADPEA: Structure-aware dual probability evolutionary adaptive algorithm for the budgeted influence maximization problemInformation Sciences10.1016/j.ins.2024.121784699(121784)Online publication date: May-2025
https://doi.org/10.1016/j.ins.2024.121784
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Information & Contributors

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Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 42, Issue 2

May 2013

64 pages

ISSN:0163-5808

DOI:10.1145/2503792

Issue’s Table of Contents

Copyright © 2013 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 July 2013

Published in SIGMOD Volume 42, Issue 2

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Cited By

Brooks HPorter M(2025)An “opinion reproduction number” for infodemics in a bounded-confidence content-spreading process on networksChaos: An Interdisciplinary Journal of Nonlinear Science10.1063/5.020643135:1Online publication date: 30-Jan-2025
https://doi.org/10.1063/5.0206431
Singh SSrivastava DVerma MMuhuri S(2025)Information diffusion analysis: process, model, deployment, and applicationThe Knowledge Engineering Review10.1017/S026988892400010939Online publication date: 22-Jan-2025
https://doi.org/10.1017/S0269888924000109
Zhu EWang HZhang YMa M(2025)SADPEA: Structure-aware dual probability evolutionary adaptive algorithm for the budgeted influence maximization problemInformation Sciences10.1016/j.ins.2024.121784699(121784)Online publication date: May-2025
https://doi.org/10.1016/j.ins.2024.121784
Lin TLuo GLi WWang W(2025)Network alignment in multiplex social networks using the information diffusion dynamicsChaos, Solitons & Fractals10.1016/j.chaos.2024.115792190(115792)Online publication date: Jan-2025
https://doi.org/10.1016/j.chaos.2024.115792
Wahid JXu MAyoub MJiang XLei SGao YHussain SYang Y(2025)AI-driven social media text analysis during crisis: A review for natural disasters and pandemicsApplied Soft Computing10.1016/j.asoc.2025.112774(112774)Online publication date: Jan-2025
https://doi.org/10.1016/j.asoc.2025.112774
Ittan MElayidom SMathew M(2024)The Social Media Influence JourneyEnhancing Communication and Decision-Making With AI10.4018/979-8-3693-9246-1.ch003(65-98)Online publication date: 27-Sep-2024
https://doi.org/10.4018/979-8-3693-9246-1.ch003
Zhu WLiu CFan SHe Z(2024)Performance Evaluation and Influencing Factors of Scientific Communication in Research InstitutionsSystems10.3390/systems1206019212:6(192)Online publication date: 30-May-2024
https://doi.org/10.3390/systems12060192
Agra ASamuco J(2024)A New Algorithm Framework for the Influence Maximization Problem Using Graph ClusteringInformation10.3390/info1502011215:2(112)Online publication date: 14-Feb-2024
https://doi.org/10.3390/info15020112
Fu SWang LYang J(2024)A review on network representation learning with multi-granularity perspectiveIntelligent Data Analysis10.3233/IDA-22732828:1(3-32)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.3233/IDA-227328
Hou DGao CLi XWang ZWooldridge MDy JNatarajan S(2024)DAG-aware variational autoencoder for social propagation graph generationProceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v38i8.28694(8508-8516)Online publication date: 20-Feb-2024
https://dl.acm.org/doi/10.1609/aaai.v38i8.28694
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