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review-article

Influence maximization frameworks, performance, challenges and directions on social network: : A theoretical study

Authors:

Shashank Sheshar Singh,

Divya Srivastva,

Madhushi Verma,

Jagendra SinghAuthors Info & Claims

Volume 34, Issue 9

Pages 7570 - 7603

https://doi.org/10.1016/j.jksuci.2021.08.009

Published: 01 October 2022 Publication History

Highlights

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The influence maximization problem aims to fetch the top influential users in the social networks.

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A brief description of diffusion models alongwith characteristic comparison is presented.

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Paper provides a comprehensive analysis on algorithmic perspective towards influential users.

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Comparative analysis of IM algorithms corresponding to their performance metrics is presented.

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Study concludes with open problems, research challenges and future research directions.

Abstract

The influence maximization (IM) problem identifies the subset of influential users in the network to provide solutions for real-world problems like outbreak detection, viral marketing, etc. Therefore, IM is an essential problem to tackle some real-life problems and activities. Accordingly, many reviews and surveys are presented, and most of them mainly focused on classical IM frameworks for single networks and avoided other IM frameworks. In this context, the IM problem still has some important design aspects along with some new challenges of the problem. Inspired by these facts, a comparative survey of the state-of-art approaches for IM algorithms is presented in this paper. To build the foundation of IM problem, firstly, the well-accepted information diffusion models are discussed. Secondly, a comprehensive study of IM algorithms along with a comparative review is presented based on algorithmic frameworks of IM algorithms. A relative analysis of IM approaches regarding performance metrics is discussed next. At last, the upcoming challenges and future prospects of the research in this field are discussed.

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Meena SSingh SSingh K(2024)DCDIMB: Dynamic Community-based Diversified Influence Maximization using Bridge NodesACM Transactions on the Web10.1145/366461818:4(1-32)Online publication date: 11-May-2024
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cover image Journal of King Saud University - Computer and Information Sciences

Journal of King Saud University - Computer and Information Sciences Volume 34, Issue 9

Oct 2022

1335 pages

ISSN:1319-1578

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King Saud University.

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Elsevier Science Inc.

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Published: 01 October 2022

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Cited By

Shelke VJadhav A(2024)Context propagation based influence maximization model for dynamic link predictionIntelligent Decision Technologies10.3233/IDT-23080418:3(2371-2387)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.3233/IDT-230804
Meena SSingh SSingh K(2024)DCDIMB: Dynamic Community-based Diversified Influence Maximization using Bridge NodesACM Transactions on the Web10.1145/366461818:4(1-32)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3664618
Singh SMuhuri SMishra SSrivastava DShakya HKumar N(2024)Social Network Analysis: A Survey on Process, Tools, and ApplicationACM Computing Surveys10.1145/364847056:8(1-39)Online publication date: 10-Apr-2024
https://dl.acm.org/doi/10.1145/3648470
Kumar MMishra SSingh SBiswas B(2024)Community-enhanced Link Prediction in Dynamic NetworksACM Transactions on the Web10.1145/358051318:2(1-32)Online publication date: 8-Jan-2024
https://dl.acm.org/doi/10.1145/3580513
Liu CXu HLiu X(2024)Online influence maximization under continuous independent cascade model with node-edge-level feedbackKnowledge and Information Systems10.1007/s10115-023-01982-866:2(1091-1110)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10115-023-01982-8
Venunath MSujatha PKoti P(2024)Identification of influential users in social media network using golden ratio optimization methodSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09218-128:3(2207-2222)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s00500-023-09218-1
Li YGao HGao YGuo JWu W(2023)A Survey on Influence Maximization: From an ML-Based Combinatorial OptimizationACM Transactions on Knowledge Discovery from Data10.1145/360455917:9(1-50)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3604559
Singh SSrivastava VKumar ATiwari SSingh DLee H(2022)Social Network Analysis: A Survey on Measure, Structure, Language Information Analysis, Privacy, and ApplicationsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/353973222:5(1-47)Online publication date: 8-Jun-2022
https://dl.acm.org/doi/10.1145/3539732

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