Modeling and Analysis of Opinion Dynamics in Social Networks Using Multiple-Population Mean Field Games

Reginald A. Banez; Hao Gao; Lixin Li; Chungang Yang; Zhu Han; H. Vincent Poor

doi:10.1109/TSIPN.2022.3166102

Modeling and Analysis of Opinion Dynamics in Social Networks Using Multiple-Population Mean Field Games

Reginald A. Banez, Hao Gao, Lixin Li, Chungang Yang, Zhu Han, H. Vincent Poor

Research output: Contribution to journal › Article › peer-review

Abstract

The dominanceof social networks has advanced immensely as many users become more dependent on these networks to be able to engage on social discussions and activities. The behavior of these users about a specific topic or issue can be extracted from their own belief or opinion as well as that of their connections. In order to derive meaningful and important behavioral information, these users can be modeled and analyzed together according to similarities in attributes such as political orientation, race, gender, and age. In this research work, the opinion dynamics of a multiple-population social network is investigated through the application of multiple-population mean field game (MPMFG) for behavior modeling and analysis. As a consequence of the proposed MPMFG model, information can be gained on the behavior of social network users belonging to different populations or groups. Specifically, the proposed MPFMG model can be utilized to estimate and predict the behavior of a social network group as well as their effect on the belief and opinion of other groups. Simulations are provided to demonstrate the belief and opinion dynamics of social network users in multiple-population settings. Moreover, theoretical and experimental results as well as comprehensive performance analysis are presented to demonstrate the effectiveness and validity of the proposed MPMFG approach in modeling and analyzing the evolution of opinions in multiple-population social networks.

Original language	American English
Pages (from-to)	301-316
Number of pages	16
Journal	IEEE Transactions on Signal and Information Processing over Networks
Volume	8
DOIs	https://doi.org/10.1109/TSIPN.2022.3166102
State	Published - 2022
Externally published	Yes

ASJC Scopus subject areas

Signal Processing
Information Systems
Computer Networks and Communications

Keywords

Belief and opinion evolution
Multiple-population mean field games
Numerical method for mean field games
Social evolution data
Social networks

Access to Document

10.1109/TSIPN.2022.3166102

Cite this

@article{2e76062a976a451787df84c8c3f0f319,

title = "Modeling and Analysis of Opinion Dynamics in Social Networks Using Multiple-Population Mean Field Games",

abstract = "The dominanceof social networks has advanced immensely as many users become more dependent on these networks to be able to engage on social discussions and activities. The behavior of these users about a specific topic or issue can be extracted from their own belief or opinion as well as that of their connections. In order to derive meaningful and important behavioral information, these users can be modeled and analyzed together according to similarities in attributes such as political orientation, race, gender, and age. In this research work, the opinion dynamics of a multiple-population social network is investigated through the application of multiple-population mean field game (MPMFG) for behavior modeling and analysis. As a consequence of the proposed MPMFG model, information can be gained on the behavior of social network users belonging to different populations or groups. Specifically, the proposed MPFMG model can be utilized to estimate and predict the behavior of a social network group as well as their effect on the belief and opinion of other groups. Simulations are provided to demonstrate the belief and opinion dynamics of social network users in multiple-population settings. Moreover, theoretical and experimental results as well as comprehensive performance analysis are presented to demonstrate the effectiveness and validity of the proposed MPMFG approach in modeling and analyzing the evolution of opinions in multiple-population social networks. ",

keywords = "Belief and opinion evolution, Multiple-population mean field games, Numerical method for mean field games, Social evolution data, Social networks",

author = "Banez, {Reginald A.} and Hao Gao and Lixin Li and Chungang Yang and Zhu Han and {Vincent Poor}, H.",

note = "Funding Information: This work was supported in part by the U.S. Air Force Office of Scientific Research under MURI Grant FA9550-18-1-0502, and in part by the U.S. MURI AFOSR under Grants MURI 18RT0073, NSF EARS-1839818, CNS-1717454, CNS-1731424, and CNS-1702850. Publisher Copyright: {\textcopyright} 2015 IEEE.",

year = "2022",

doi = "10.1109/TSIPN.2022.3166102",

language = "American English",

volume = "8",

pages = "301--316",

journal = "IEEE Transactions on Signal and Information Processing over Networks",

issn = "2373-776X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Modeling and Analysis of Opinion Dynamics in Social Networks Using Multiple-Population Mean Field Games

AU - Banez, Reginald A.

AU - Gao, Hao

AU - Li, Lixin

AU - Yang, Chungang

AU - Han, Zhu

AU - Vincent Poor, H.

N1 - Funding Information: This work was supported in part by the U.S. Air Force Office of Scientific Research under MURI Grant FA9550-18-1-0502, and in part by the U.S. MURI AFOSR under Grants MURI 18RT0073, NSF EARS-1839818, CNS-1717454, CNS-1731424, and CNS-1702850. Publisher Copyright: © 2015 IEEE.

PY - 2022

Y1 - 2022

N2 - The dominanceof social networks has advanced immensely as many users become more dependent on these networks to be able to engage on social discussions and activities. The behavior of these users about a specific topic or issue can be extracted from their own belief or opinion as well as that of their connections. In order to derive meaningful and important behavioral information, these users can be modeled and analyzed together according to similarities in attributes such as political orientation, race, gender, and age. In this research work, the opinion dynamics of a multiple-population social network is investigated through the application of multiple-population mean field game (MPMFG) for behavior modeling and analysis. As a consequence of the proposed MPMFG model, information can be gained on the behavior of social network users belonging to different populations or groups. Specifically, the proposed MPFMG model can be utilized to estimate and predict the behavior of a social network group as well as their effect on the belief and opinion of other groups. Simulations are provided to demonstrate the belief and opinion dynamics of social network users in multiple-population settings. Moreover, theoretical and experimental results as well as comprehensive performance analysis are presented to demonstrate the effectiveness and validity of the proposed MPMFG approach in modeling and analyzing the evolution of opinions in multiple-population social networks.

AB - The dominanceof social networks has advanced immensely as many users become more dependent on these networks to be able to engage on social discussions and activities. The behavior of these users about a specific topic or issue can be extracted from their own belief or opinion as well as that of their connections. In order to derive meaningful and important behavioral information, these users can be modeled and analyzed together according to similarities in attributes such as political orientation, race, gender, and age. In this research work, the opinion dynamics of a multiple-population social network is investigated through the application of multiple-population mean field game (MPMFG) for behavior modeling and analysis. As a consequence of the proposed MPMFG model, information can be gained on the behavior of social network users belonging to different populations or groups. Specifically, the proposed MPFMG model can be utilized to estimate and predict the behavior of a social network group as well as their effect on the belief and opinion of other groups. Simulations are provided to demonstrate the belief and opinion dynamics of social network users in multiple-population settings. Moreover, theoretical and experimental results as well as comprehensive performance analysis are presented to demonstrate the effectiveness and validity of the proposed MPMFG approach in modeling and analyzing the evolution of opinions in multiple-population social networks.

KW - Belief and opinion evolution

KW - Multiple-population mean field games

KW - Numerical method for mean field games

KW - Social evolution data

KW - Social networks

UR - http://www.scopus.com/inward/record.url?scp=85128296699&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85128296699&partnerID=8YFLogxK

U2 - 10.1109/TSIPN.2022.3166102

DO - 10.1109/TSIPN.2022.3166102

M3 - Article

SN - 2373-776X

VL - 8

SP - 301

EP - 316

JO - IEEE Transactions on Signal and Information Processing over Networks

JF - IEEE Transactions on Signal and Information Processing over Networks

ER -

Modeling and Analysis of Opinion Dynamics in Social Networks Using Multiple-Population Mean Field Games

Abstract

ASJC Scopus subject areas

Keywords

Access to Document

Other files and links

Cite this