数据驱动的大群体应急决策公众专家动态协同方法

doi:10.12305/j.issn.1001-506X.2023.12.17

摘要/Abstract

摘要：

针对大群体应急决策中环境复杂多变及公众参与度较低的问题, 提出一种数据分析驱动的大群体应急决策公众专家动态协同方法。首先, 通过对社交媒体平台中的文本数据进行情感分析, 分别从属性层和综合层评价大群体应急决策质量; 其次, 根据属性层决策质量提出了属性权重动态更新规则; 然后, 在社会网络环境下基于综合决策质量及专家偏好与群体偏好的距离动态更新专家间的信任关系, 并使用改进PageRank算法计算专家权重; 最后, 通过某飞行器事故的案例应用和对比分析验证了所提方法的有效性和优越性。

关键词: 社交媒体数据, 情感分析, 大群体应急决策, 动态协同, 飞行器事故

Abstract:

Aiming at the complex and changeable environment and the low public participation in large-group emergency decision-making, a data-driven dynamic collaborative method of public and experts in large-group emergency decision-making is proposed. Firstly, the sentiment analysis is carried out on text data in social media platforms to evaluate the quality of large-group emergency decision-making from attribute level and comprehensive level respectively. Secondly, according to the decision-making quality of attribute level, the dynamic update rules of attribute weight are proposed. Then, under the social network environment, the trust relationship between different experts is dynamically updated based on the comprehensive quality of decision-making and the distance between experts'preference and groups preference, and the expert weight is calculated by the PageRank algorithm. Finally, the effectiveness and superiority of the proposed method are verified through the case application and comparative analysis of an aircraft accident.

Key words: social media data, sentiment analysis, large-group emergency decision-making, dynamic collaboration, aircraft accident

中图分类号:

N945

徐选华, 朱昱承. 数据驱动的大群体应急决策公众专家动态协同方法[J]. 系统工程与电子技术, 2023, 45(12): 3875-3886.

Xuanhua XU, Yucheng ZHU. Data-driven dynamic collaborative method of public and experts in large-group emergency decision-making[J]. Systems Engineering and Electronics, 2023, 45(12): 3875-3886.

图/表 19

表1

表2

图1

表3

图2

表4

表5

表6

表7

表8

表9

表10

表11

表12

表13

表14

表15

表16

图3

参考文献 43

1	徐选华. 大数据环境下复杂大群体决策理论方法及应用[M]. 北京: 科学出版社, 2020.
	XU X H . Complex large group decision making: theory, methods and applications based on big data analytics[M]. Beijing: Science Press, 2020.
2	徐选华, 尹儇鹏, 钟香玉, 等. 大群体决策理论与方法研究综述: 问题与挑战[J]. 信息与控制, 2021, 50 (1): 54-64, 74.
	XU X H , YIN X P , ZHONG X Y , et al. Summary of research on theory and methods in large-group decision-making: problems and challenges[J]. Information and Control, 2021, 50 (1): 54-64, 74.
3	SCHWARZ A . How publics use social media to respond to blame games in crisis communication: the love parade tragedy in Duisburg 2010[J]. Public Relations Review, 2012, 38 (3): 430- 437. doi: 10.1016/j.pubrev.2012.01.009
4	郭杨, 王璐, 陈超亿, 等. 辽吉两地突发应急工作依据公众需要科学决策程度比较[J]. 中国公共卫生, 2021, 37 (8): 1297- 1300.
	GUO Y , WANG L , CHEN C Y , et al. Comparison of public needs-based scientific decision-making in healthemergency management between Liaoning and Jilin province: aliterature study[J]. Chinese Journal of Public Health, 2021, 37 (8): 1297- 1300.
5	LIU J , LIU L Y , TU Y , et al. Multi-stage Internet public opinion risk grading analysis of public health emergencies: an empirical study on Microblog in COVID-19[J]. Information Processing & Management, 2022, 59 (1): 102796.
6	ZHOU C , XIU H X , WANG Y Q , et al. Characterizing the dissemination of misinformation on social media in health emergencies: an empirical study based on COVID-19[J]. Information Processing & Management, 2021, 58 (4): 102544.
7	VILLODRE J , CRIADO J I . User roles for emergency management in social media: Understanding actors'behavior during the 2018 Majorca Island flash floods[J]. Government Information Quarterly, 2020, 37 (4): 101521. doi: 10.1016/j.giq.2020.101521
8	康伟. 基于SNA的突发事件网络舆情关键节点识别——以"7·23动车事故" 为例[J]. 公共管理学报, 2012, 9 (3): 101- 111. doi: 10.3969/j.issn.1672-6162.2012.03.011
	KANG W . Analysis of the key nodes in public opinion spread during emergencies based on social network theory—a case study of the 7·23 Wenzhou high-speed train collision[J]. Journal of Public Management, 2012, 9 (3): 101- 111. doi: 10.3969/j.issn.1672-6162.2012.03.011
9	徐选华, 杨玉珊, 陈晓红. 基于决策者风险偏好大数据分析的大群体应急决策方法[J]. 运筹与管理, 2019, 28 (7): 1- 10.
	XU X H , YANG Y S , CHEN X H . The large group emergency decision making method based on large data analysis of risk pre-ference of decision-makers[J]. Operations Research and Manage- ment Science, 2019, 28 (7): 1- 10.
10	XU X H , YIN X P , CHEN X H . A large-group emergency risk decision method based on data mining of public attribute preferences[J]. Knowledge-based Systems, 2018, 163, 495- 509.
11	CHEN X H , ZHANG W W , XU X H , et al. A public and large-scale expert information fusion method and its application: Mining public opinion via sentiment analysis and measuring public dynamic reliability[J]. Information Fusion, 2022, 78, 71- 85. doi: 10.1016/j.inffus.2021.09.015
12	杨乐. 互联网时代应急决策的理念与策略探析[J]. 领导科学, 2019, (18): 40- 42.
	YANG L . A probe into the idea and strategy of emergency deci-sion-making in the Internet era[J]. Leadership Science, 2019, (18): 40- 42.
13	徐选华, 钟香玉, 周艳菊. 基于退出-委托动态冲突消解机制的应急大群体决策方法[J]. 控制与决策, 2015, 30 (9): 1583- 1590.
	XU X H , ZHONG X Y , ZHOU Y J . Emergency large group decision method based on exit-commission dynamic conflict eliminating mechanism[J]. Control and Decision, 2015, 30 (9): 1583- 1590.
14	尹儇鹏, 徐选华, 陈晓红. 基于多主体仿真的大群体应急决策风险致因分析[J]. 中国管理科学, 2020, 28 (2): 208- 219.
	YIN X P , XU X H , CHEN X H . Risk-causing analysis of large-group emergency decision-making based on multi-agent simulation[J]. Chinese Journal of Management Science, 2020, 28 (2): 208- 219.
15	徐选华, 马志鹏, 陈晓红. 大群体冲突、风险感知与应急决策质量的关系研究: 决策犹豫度的调节作用[J]. 管理工程学报, 2020, 34 (6): 90- 99.
	XU X H , MA Z P , CHEN X H . Research on the relationship among large group conflict, risk perception and emergency decision quality: the moderating effect of decision hesitation[J]. Journal of Industrial Engineering and Engineering Management, 2020, 34 (6): 90- 99.
16	XU X H , ZHANG Q H , CHEN X H . Consensus-based non-cooperative behaviors management in large-group emergency decision-making considering experts' trust relations and preference risks[J]. Knowledge-based Systems, 2020, 190, 105108. doi: 10.1016/j.knosys.2019.105108
17	徐选华, 马志鹏. 基于公众偏好大数据分析的大群体应急决策质量动态演化研究[J]. 中国管理科学, 2022, 30 (7): 140- 149.
	XU X H , MA Z P . Dynamic evolution research on emergency decision quality of large group based on the public preferences big data[J]. Chinese Journal of Management Science, 2022, 30 (7): 140- 149.
18	WAN Q F , XU X H , ZHUANG J , et al. A sentiment analysis-based expert weight determination method for large-scale group decision-making driven by social media data[J]. Expert Systems with Applications, 2021, 185, 115629.
19	PANG Q , WANG H , XU Z S . Probabilistic linguistic term sets in multi-attribute group decision making[J]. Information Sciences, 2016, 369, 128- 143.
20	LIAO H C , JIANG L S , XU Z S , et al. A linear programming method for multiple criteria decision making with probabilistic linguistic information[J]. Information Science, 2017, 4151416, 341- 355.
21	MAO X B , WU M , DONG J Y , et al. A new method for probabilistic linguistic multi-attribute group decision making: application to the selection of financial technologies[J]. Applied Soft Computing, 2019, 77, 155- 175.
22	SERRANO-GUERRERO J , OLIVAS J A , ROMERO F P , et al. Sentiment analysis: a review and comparative analysis of web services[J]. Information Sciences, 2015, 311, 18- 38.
23	张瑾, 尤天慧. 考虑消费者期望的多属性在线评论商品选择方法[J]. 管理工程学报, 2020, 34 (5): 24- 31.
	ZHANG J , YOU T H . Method for selecting desirable product(s) through multiple attribute online reviews considering customer's aspirations[J]. Journal of Industrial Engineering and Engineering Management, 2020, 34 (5): 24- 31.
24	LI X D , WU P J , ZOU C X , et al. Sentiment lossless summarization[J]. Knowledge-based Systems, 2021, 227, 107170.
25	GRIDACH M . A framework based on (probabilistic) soft logic and neural network for NLP[J]. Applied Soft Computing, 2020, 93, 106232.
26	LANE P C R , CLARKE D , HENDER P . On developing robust models for favourability analysis: model choice, feature sets and imbalanced data[J]. Decision Support Systems, 2012, 53 (4): 712- 718.
27	MELTON C A , OLUSANYA O A , AMMAR N , et al. Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the reddit social media platform: a call to action for strengthening vaccine confidence[J]. Journal of Infection and Public Health, 2021, 14 (10): 1505- 1512.
28	PATHAK A R , PANDEY M , RAUTARAY S . Topic-level sentiment analysis of social media data using deep learning[J]. Applied Soft Computing, 2021, 108, 107440.
29	VASHISHTHA S , SUSAN S . Fuzzy rule based unsupervised sentiment analysis from social media posts[J]. Expert Systems with Applications, 2019, 138, 112834.
30	GUTIÉRREZ-BATISTA K , VILA M A , MARTIN-BAUTISTA M J . Building a fuzzy sentiment dimension for multidimensional analysis in social networks[J]. Applied Soft Computing, 2021, 108, 107390.
31	DAHOOIE J H , RAAFAT R , QORBANI A R , et al. An intui- tionistic fuzzy data-driven product ranking model using sentiment analysis and multi-criteria decision-making[J]. Technological Forecasting and Social Change, 2021, 173, 121158.
32	ZUHEROS C , MARTÍNEZ-CÁMARA E , HERRERA-VIEDMA E , et al. Sentiment analysis based multi-person multi-criteria decision making methodology using natural language processing and deep learning for smarter decision aid case study of restaurant choice using TripAdvisor reviews[J]. Information Fusion, 2021, 68, 22- 36.
33	WU J , CHICLANA F , FUJITA H , et al. A visual interaction consensus model for social network group decision making with trust propagation[J]. Knowledge-based Systems, 2017, 122, 39- 50.
34	WU N N , XU Y J , LIU X , et al. Water-energy-food nexus evaluation with a social network group decision making approach based on hesitant fuzzy preference relations[J]. Applied Soft Computing, 2020, 93, 106363.
35	ZHANG H J , PALOMARES I , DONG Y C , et al. Managing non-cooperative behaviors in consensus-based multiple attribute group decision making: an approach based on social network analysis[J]. Knowledge-based Systems, 2018, 162, 29- 45.
36	HOGENBOOM A , BOON F , FRASINCAR F . A statistical approach to star rating classification of sentiment[J]. Advances in Intelligent Systems & Computing, 2012, 171, 251- 260.
37	李欣苗, 陈云. 基于特征选择和倾向分析联合优化的UGC情感自动识别方法[J]. 管理工程学报, 2019, 33 (2): 61- 71.
	LI X M , CHEN Y . UGC sentiment analysis method based on feature selection and sentiment classification optimization[J]. Journal of Industrial Engineering and Engineering Management, 2019, 33 (2): 61- 71.
38	SONG C , WANG X K , CHENG P F , et al. SACPC: a framework based on probabilistic linguistic terms for short text sentiment analysis[J]. Knowledge-based Systems, 2020, 194, 105572.
39	曾守桢, 胡英杰. 基于高度残缺信息的分布式语言信任网络群决策方法[J]. 系统工程与电子技术, 2022, 44 (6): 1907- 1919.
	ZENG S Z , HU Y J . Group decision making method for distri-buted linguistic trust network based on highly incomplete information[J]. Systems Engineering and Electronics, 2022, 44 (6): 1907- 1919.
40	CHU J F , WANG Y M , LIU X W , et al. Social network community analysis based large-scale group decision making approach with incomplete fuzzy preference relations[J]. Information Fusion, 2020, 60, 98- 120.
41	PAGE L, BRIN S, MOTWANI R, et al. The pagerank citation ranking: bringing order to the web[R]. California: Stanford Digtal Library, 1998.
42	XU X H , WANG L L , CHEN X H , et al. Large group emergency decision-making method with linguistic risk appetites based on criteria mining[J]. Knowledge-based Systems, 2019, 182, 104849.
43	徐选华, 刘尚龙. 考虑时间序列的动态大群体应急决策方法[J]. 控制与决策, 2020, 35 (11): 2609- 2618.
	XU X H , LIU S L . Dynamic large group emergency decision-making method considering time series[J]. Control and Decision, 2020, 35 (11): 2609- 2618.

变量符号	变量含义
E={e_i\|i=1, 2, …, M}	专家集合
X={x_l\|l=1, 2, …, P}	备选方案集合
C={c_j\|j=1, 2, …, N}	属性集合
t=0, 1, …, T	决策阶段, 其中T代表阶段总数
Ω^t=(ω_i^t, i=1, 2, …, M)	专家权重向量, 其中ω_i^t代表专家e_i在阶段t时的权重, 满足 $ \sum_{i=1}^{M} \omega_{i}^{t}=1$
W^t=(w_j^t, j=1, 2, …, N)	属性权重向量, 其中w_j^t代表属性c_j在阶段t时的权重, 满足 $ \sum_{j=1}^{N} w_{j}^{t}=1$
A^ti=(L_lj^ti(p))_P×N	专家e_i的评价矩阵, 其中L_lj^ti(P)为概率语言术语集, 代表专家e_i在阶段t时对方案x_l关于属性c_j的评价值
G^t(E, B)	阶段t时专家的社会网络

变量符号	变量含义
P^t={p_h^t\|h=1, 2, …, H_t}	社交媒体中突发事件相关的帖子集合
V^j={v_k^j\|k=1, 2, …, K_j}	属性c_j相关的关键词集合
U^th={u_s^th\|s=1, 2, …, S_th}	帖子p_h^t的分词列表
P^tj={p_h^tj\|h=1, 2, …, H_tj}	P^t中有关属性c_j的帖子集合

情感分类	情感得分
s₀	[0, 0.2)
s₁	[0.2, 0.4)
s₂	[0.4, 0.6)
s₃	[0.6, 0.8)
s₄	[0.8, 1]

ω₁⁰	ω₂⁰	…	ω₁₉⁰	ω₂₀⁰
0.042 4	0.026 9	…	0.053 1	0.063 0

属性	关键词	关键词数量
人员搜救	搜救、救援、生命、勘察、遇难、人员、…、消防员、旅客、幸存者、安全、找到	31
安置与善后	家属、亲人、噩耗、赔偿、接待、安置、…、心理、保险、遗物、妥善、家庭	26
舆情管理	传播、宣传、散播、转发、谣言、公布、…、发布会、新闻、微博、消息、报道	28
事故原因及追责	原因、调查、责任、黑匣子、分析、检验、…、无线电、真相、追责、译码、技术	30
时效性	突发、紧急、应急、响应、争分夺秒、第一时间、…、迅速、火速、启动、应急、响应、指挥	24