社会网络行为数据驱动的大群体应急决策共识模型

doi:10.12305/j.issn.1001-506X.2023.07.19

Abstract

Abstract:

Aiming at the problems of insufficient decision-making reference information and difficulty in reaching consensus in large-group emergency decision-making, a large-group emergency decision-making consensus model driven by social network behavior data is constructed. Firstly, in view of the lack of decision-making reference information, an attribute mining method based on public behavior big data analysis is proposed. The proposed method takes public attention as the data clustering standard, and mines the topics and weights of public concern topic in social media data as decision reference information to participate in the large group emergency decision-making process. Secondly, considering the difficulty in reaching consensus in large group, a decision consensus model based on trust-similarity analysis is established. Based on expert social network clustering, the proposed model introduces confidence coefficient and retention coefficient, and designs consensus feedback rules to adjust experts'preferences and improves the level of group consensus. As a result, the proposed model is applied to a public security incident case to verify its feasibility and rationality.

Key words: social network, behavior data, large group, public security, emergency decision-making

CLC Number:

N945

Xuanhua XU, Ting XIAO. Consensus model for large group emergency decision-making driven by social network behavior data[J]. Systems Engineering and Electronics, 2023, 45(7): 2086-2097.

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References 43

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社会关系矩阵	网络关系图	代数式表示
$ \begin{array}{c} \boldsymbol{T}=\left[t_{i-j}\right]=\\ \left[\begin{array}{cccc} 0 & 0.4 & 0 & 1 \\ 0 & 0 & 0 & 0 \\ 0.7 & 0.2 & 0 & 0 \\ 0 & 0 & 0.3 & 0 \end{array}\right] \end{array}$		e₁Re₂, e₁Re₄, e₃Re₁, e₃Re₂, e₄Re₃

信息	点赞	评论	转发
数量指标权重	290 036	94 987	54 378
数量指标权重	0.107	0.325	0.568

数据集	DS_i(LN)	DS_i(CN)	DS_i(FN)	关注系数
DS₁	220	60	47	0.690
DS₂	76	25	12	0.232
DS₃	12	5	4	0.078

属性	关键词	ω(DS₁)	ω(DS₂)	ω(DS₃)	ω
实施保障	医护人员、奔赴前线、援助等	0.135	0.428	0.470	0.229
感染风险	干咳、发烧、呼吸困难等	0.329	0.130	0.183	0.271
监测控制	指挥、防控、专题会议等	0.242	0.218	0.080	0.224
生活影响	复工、封城、返岗等	0.295	0.224	0.267	0.276

聚集	人数	聚集权重	专家组成
C¹	4	0.21	{e₃, e₄, e₇, e₁₄}
C²	6	0.29	{e₂, e₅, e₈, e₁₁, e₁₈, e₂₀}
C³	4	0.20	{e₆, e₁₀, e₁₃, e₁₅}
C⁴	6	0.30	{e₁, e₉, e₁₂, e₁₆, e₁₇, e₁₉}

Consensus model for large group emergency decision-making driven by social network behavior data

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专家	D_in	D_out	C(e_i)	w_i	专家	D_in	D_out	C(e_i)	w_i
e₁	0.029 8	0.017 9	0.842 1	0.164	e₂	0.029 8	0.011 9	0.789 5	0.140
e₃	0.029 8	0.023 8	0.868 4	0.260	e₄	0.029 8	0.029 7	0.815 8	0.275
e₅	0.035 7	0.023 8	0.763 2	0.176	e₆	0.017 9	0.029 7	0.924 8	0.261
e₇	0.029 8	0.005 9	0.789 5	0.205	e₈	0.035 7	0.029 7	0.763 2	0.191
e₉	0.017 9	0.047 6	0.789 5	0.203	e₁₀	0.023 8	0.023 8	0.815 8	0.257
e₁₁	0.023 8	0.047 6	0.952 6	0.194	e₁₂	0.017 9	0.023 8	0.736 9	0.156
e₁₃	0.041 7	0.005 9	0.842 1	0.237	e₁₄	0.017 9	0.035 7	0.868 4	0.260
e₁₅	0.017 9	0.023 8	0.736 9	0.245	e₁₆	0.029 8	0.023 8	0.763 2	0.186
e₁₇	0.023 8	0.017 8	0.763 2	0.151	e₁₈	0.023 8	0.029 7	0.868 4	0.169
e₁₉	0.006 0	0.029 8	0.842 1	0.141	e₂₀	0.017 9	0.017 8	0.868 4	0.130

轮次	CL(C¹)	CL(C²)	CL(C³)	CL(C⁴)	GCL	调节聚集	调节系数
0	0.893	0.897	0.919	0.900	0.902	C¹	γ₃=0.416, γ₄=0.433, γ₇=0.403, γ₁₄=0.370
1	0.924	0.902	0.918	0.903	0.912	C²	γ₂=0.408, γ₅=0.394, γ₈=0.338, γ₁₁=0.376, γ₁₈=0.349, γ₂₀=0.409
2	0.938	0.944	0.925	0.921	0.932	C⁴	γ₁=0.388, γ₉=0.234, γ₁₂=0.408, γ₁₆=0.403, γ₁₇=0.398, γ₁₉=0.292
3	0.945	0.949	0.924	0.935	0.938	C³	γ₆=0.365, γ₄=0.365, γ₁₃=0.414, γ₁₅=0.398
4	0.948	0.949	0.967	0.941	0.951	-	-

方案	c₁	c₂	c₃	c₄
x₁	〈0.38, 0.30〉	〈0.22, 0.40〉	〈0.28, 0.41〉	〈0.29, 0.31〉
x₂	〈0.29, 0.40〉	〈0.32, 0.36〉	〈0.35, 0.29〉	〈0.39, 0.27〉
x₃	〈0.39, 0.27〉	〈0.32, 0.26〉	〈0.32, 0.34〉	〈0.35, 0.30〉

方法	属性权重	方案排序结果
文献[33]	(0.314, 0.282, 0.214, 0.190)	x₃$ \succ $x₁$ \succ $x₂
本文	(0.229, 0.271, 0.224, 0.278)	x₃$ \succ $x₂$ \succ $x₁

方法	调整次数	调整专家人数	调节参数	方案排序结果
文献[42]	2	8~11	主观确定	x₂$ \succ $x₃$ \succ $x₁
文献[43]	4	4~9	主观确定	x₃$ \succ $x₂$ \succ $x₁
本文	4	4~6	客观确定	x₃$ \succ $x₂$ \succ $x₁

考虑因素	调整次数	共识水平	共识平均增长速度/%	方案排序
信任关系	6	GCL₀=0.902;GCL₁=0.909;GCL₂=0.922;GCL₃=0.936;GCL₄=0.940;GCL₅=0.946;GCL₆=0.953	0.85	x₃$ \succ $x₂$ \succ $x₁
相似关系	5	GCL₀=0.902;GCL₁=0.910;GCL₂=0.923;GCL₃=0.936;GCL₄=0.946;GCL₅=0.950	0.86	x₃$ \succ $x₂$ \succ $x₁
信任-相似	4	GCL₀=0.902;GCL₁=0.912;GCL₂=0.932;GCL₃=0.938;GCL₄=0.951	1.19	x₃$ \succ $x₂$ \succ $x₁

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