research-article

Information propagation model based on hybrid social factors of opportunity, trust and motivation

Authors:

Xiaoliang Chen,

Mengmeng JiaAuthors Info & Claims

Volume 333, Issue C

Pages 169 - 184

https://doi.org/10.1016/j.neucom.2018.12.062

Published: 14 March 2019 Publication History

Abstract

The propagation of information in the network is a complex dynamic process. Establishing an accurate information propagation model around common social factors benefits a lot from its evolution simulation for identifying the valuable information and regulating public opinions. In this paper, we propose Opportunity, Social Trust and Game Choice Motivation relying on triadic closure principle in social network and construct a novel information propagation model with respect to combine these three types of social factors. Firstly, the interest similarity between two users is convenient for measuring the opportunity to receive certain information. Secondly, the threshold of social trust is calculated by coupling users’ network influence and content contribution. Thirdly, game choice with a rule to compute the best benefits has recognized as the motivation of users to spread a message. Finally, the game choice information propagation model based on page rank algorithm (GCIP-Page Rank) is proposed. The experimental results show that information propagation led by users experiences such stages as information contact, information trust and information propagation. At the same time, users’ social trust can accelerate the spread of information in microblog social network by considering both the network structure and information content simultaneously.

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Cited By

Huang QSi Y(2024)Blockchain-based autonomous decentralized trust management for social networkThe Journal of Supercomputing10.1007/s11227-024-06024-w80:10(14725-14751)Online publication date: 1-Jul-2024
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Zhu NLi WPan SJin SHe J(2024)Modeling the dissemination of privacy information in online social networksTransactions on Emerging Telecommunications Technologies10.1002/ett.498935:6Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1002/ett.4989
Gaeta ALoia VLomasto LOrciuoli F(2023)A novel approach based on rough set theory for analyzing information disorderApplied Intelligence10.1007/s10489-022-04283-953:12(15993-16014)Online publication date: 1-Jun-2023
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Information propagation model based on hybrid social factors of opportunity, trust and motivation

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Published In

cover image Neurocomputing

Neurocomputing Volume 333, Issue C

Mar 2019

452 pages

ISSN:0925-2312

Issue’s Table of Contents

Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 14 March 2019

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Cited By

Huang QSi Y(2024)Blockchain-based autonomous decentralized trust management for social networkThe Journal of Supercomputing10.1007/s11227-024-06024-w80:10(14725-14751)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s11227-024-06024-w
Zhu NLi WPan SJin SHe J(2024)Modeling the dissemination of privacy information in online social networksTransactions on Emerging Telecommunications Technologies10.1002/ett.498935:6Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1002/ett.4989
Gaeta ALoia VLomasto LOrciuoli F(2023)A novel approach based on rough set theory for analyzing information disorderApplied Intelligence10.1007/s10489-022-04283-953:12(15993-16014)Online publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1007/s10489-022-04283-9
Yang MChen XChen BLu PDu Y(2023)DNETC: dynamic network embedding preserving both triadic closure evolution and community structuresKnowledge and Information Systems10.1007/s10115-022-01792-465:3(1129-1157)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1007/s10115-022-01792-4
Chen JYang HLiu ZLiu MLiu M(2022)A Multi-Source Information Dissemination Model Based on Edge Evolution GameProceedings of the 2022 5th International Conference on Machine Learning and Machine Intelligence10.1145/3568199.3568226(166-174)Online publication date: 23-Sep-2022
https://dl.acm.org/doi/10.1145/3568199.3568226

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