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社会偏好理论视角下个人收入对舆论极化的影响。

Public Opinion Polarization by Individual Revenue from the Social Preference Theory.

机构信息

School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China.

School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.

出版信息

Int J Environ Res Public Health. 2020 Feb 4;17(3):946. doi: 10.3390/ijerph17030946.

DOI:10.3390/ijerph17030946
PMID:32033012
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7037295/
Abstract

Social conflicts occur frequently duringthe social transition period and the polarization of public opinion happens occasionally. By introducing the social preference theory, the target of this paper is to reveal the micro-interaction mechanism of public opinion polarization. Firstly, we divide the social preferences of Internet users (network nodes) into three categories: egoistic, altruistic, and fair preferences, and adopt the revenue function to define the benefits obtained by individuals with different preferences among their interaction process so as to analyze their decision-making behaviors driven by the revenue. Secondly, the revenue function is used to judge the exit rules of nodes in a network, and then a dynamic network of spreading public opinionwith the node (individual) exit mechanism is built based on a BA scale-free network. Subsequently, the influences of different social preferences,as well as individual revenue on the effect of public opinionpolarization, are analyzed through simulation experiments. The simulation results show that(1) Different social preferences demonstrate different influences on the evolution of public opinions, (2) Individuals tend to interact with ones with different preferences, (3) The network with a single preference or a high aggregation is more likely to form public opinion polarization. Finally, the practicability and effectiveness of the proposed model are verified by a real case.

摘要

社会转型期社会冲突频发,舆论极化偶有发生。本文引入社会偏好理论,旨在揭示舆论极化的微观互动机制。首先,我们将互联网用户(网络节点)的社会偏好分为三种类型:自利偏好、利他偏好和公平偏好,并采用收益函数来定义不同偏好的个体在相互作用过程中所获得的利益,从而分析其受收益驱动的决策行为。其次,利用收益函数判断节点在网络中的退出规则,然后基于 BA 无标度网络构建带有节点(个体)退出机制的舆论动态传播网络。随后,通过仿真实验分析了不同社会偏好和个体收益对舆论极化效应的影响。仿真结果表明:(1)不同的社会偏好对舆论的演变有不同的影响;(2)个体倾向于与具有不同偏好的个体进行互动;(3)具有单一偏好或高聚集度的网络更容易形成舆论极化。最后,通过一个真实案例验证了所提出模型的实用性和有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/b399bec85902/ijerph-17-00946-g027.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/39dd81643553/ijerph-17-00946-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/41571a9a6904/ijerph-17-00946-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/d0e27baed6ac/ijerph-17-00946-g019a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/e7be620146bd/ijerph-17-00946-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/43f7cfafd97e/ijerph-17-00946-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/745c8018ab85/ijerph-17-00946-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/e0c3e3498eb0/ijerph-17-00946-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/c5ee651d0a6d/ijerph-17-00946-g024.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/ffcd543c5a38/ijerph-17-00946-g025.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/e0627e33d02e/ijerph-17-00946-g026.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/b399bec85902/ijerph-17-00946-g027.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/39dd81643553/ijerph-17-00946-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/41571a9a6904/ijerph-17-00946-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/d0e27baed6ac/ijerph-17-00946-g019a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/e7be620146bd/ijerph-17-00946-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/43f7cfafd97e/ijerph-17-00946-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/745c8018ab85/ijerph-17-00946-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/e0c3e3498eb0/ijerph-17-00946-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/c5ee651d0a6d/ijerph-17-00946-g024.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/ffcd543c5a38/ijerph-17-00946-g025.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/e0627e33d02e/ijerph-17-00946-g026.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73c9/7037295/b399bec85902/ijerph-17-00946-g027.jpg

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4
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7
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4
Group decision-making model with incomplete fuzzy preference relations based on additive consistency.基于加法一致性的具有不完全模糊偏好关系的群体决策模型
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5
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Phys Rev Lett. 2001 Dec 31;87(27 Pt 1):278701. doi: 10.1103/PhysRevLett.87.278701. Epub 2001 Dec 12.