基于元胞自动机的网络信息传播和舆情干预机制研究

›› 2016, Vol. 28 ›› Issue (8): 106-114.

基于元胞自动机的网络信息传播和舆情干预机制研究

邓青¹, 刘艺², 马亚萍¹, 张辉¹

1. 清华大学工程物理系, 公共安全研究院, 北京 100084;
2. 中国人民公安大学治安学院, 北京 100038

收稿日期:2016-05-13 出版日期:2016-08-28 发布日期:2016-09-24
通讯作者: 刘艺(通讯作者),中国人民公安大学治安学院讲师,博士
作者简介:邓青,清华大学工程物理系博士研究生;马亚萍,清华大学工程物理系博士研究生;张辉,清华大学工程物理系教授,博士生导师,博士
基金资助:
国家自然科学基金项目（91224008）。

Information Propagation and Intervention on Online Social Networks Using Cellular Automata

Deng Qing¹, Liu Yi², Ma Yaping¹, Zhang Hui¹

1. Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084;
2. PubicOrder School, People's Public Security University of China, Beijing 100038

Received:2016-05-13 Online:2016-08-28 Published:2016-09-24

摘要/Abstract

摘要：

社交媒体的信息发布和转发机制使得信息传播速度越来越快，影响范围越来越广，也使得政府的应急处置面临前所未有的压力。目前，已有的舆情信息传播与决策模型研究主要基于两个方面：一是传染病传播模型，二是多属性模型，但很少有模型考虑了用户的个体特性和来自其他用户的影响。本文则结合用户个性从三个方面探讨舆情传播和干预机制：（1）来自周围邻居的影响；（2）用户自身对新信息的抵抗力；（3）外界环境的影响。研究方法基于元胞自动机模型对这些影响因素展开定量研究，并探讨这些影响因素对舆情传播和干预机制的影响。研究分为两个阶段，分别是舆情无干预自由扩散阶段和舆情干预阶段。在舆情干预阶段，主要探讨舆情干预措施强度和舆情干预措施实施的不同时间点对舆情传播的影响。基于这些研究以期对政府的网上危机处置提供决策支持。

关键词: 元胞自动机, 网络舆情, 信息传播, 社会关系

Abstract:

Online crisis happens so frequently that many researchers and experts have developed various models to explore information propagation mechanism. Existing information propagation models were mainly based on epidemiology or some features affected information propagation. However, few models considered the influence from neighbors or user's own resistance, which had influence on information propagation. These factors are discussed in this paper and they are(1) influence from neighbors, (2) user's own resistance, and (3) outside environment. The information propagation cellular automata model is developed in this paper to study information propagation and intervention mechanism based on these factors. Their impacts on information propagation and intervention are analyzed. The study is classified into two stages:information diffusion stage and information intervention stage. More attention is paid to the impact of intervention intensity and intervention time on the information propagation. Some inspirations are drawn based on analysis on the impacts of these factors on information controlling to support government online crisis response.

Key words: cellular automata, online crisis, information propagation, social relationship

邓青, 刘艺, 马亚萍, 张辉. 基于元胞自动机的网络信息传播和舆情干预机制研究[J]. , 2016, 28(8): 106-114.

Deng Qing, Liu Yi, Ma Yaping, Zhang Hui. Information Propagation and Intervention on Online Social Networks Using Cellular Automata[J]. , 2016, 28(8): 106-114.

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