越览（124）——精读期刊论文的引言

摘要：This issue will introduce the introduction of the intensively read replica paper "Crowd intelligence knowledge mining method based

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《基于共词网络的群智知识挖掘方法

——在应急决策中应用》的

引言”。

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Today, the editor brings the

＂Yue Lan (124)：Intensive reading of the journal article

＇Crowd intelligence knowledge mining method

based on co-word network – application

in emergency decision-making’

introduction".

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一、内容摘要（Summary of Content）

本期推文将从思维导图、精读内容、知识补充三个方面介绍精读复刻论文《基于共词网络的群智知识挖掘方法——在应急决策中应用》的引言。

This issue will introduce the introduction of the intensively read replica paper "Crowd intelligence knowledge mining method based on co-word network– application in emergency decision-making" in terms of mind maps, intensively read content, and knowledge supplementation.

二、思维导图（Mind Mapping）

三、精读内容（Intensive reading content）

（一）研究背景（Research background）

作者首先介绍了本文的研究被拒绝：近年来，我国频繁发生特大公共安全突发事件，如疫苗案件、爆炸事故、沉船事故及新冠疫情等，造成严重损失并威胁社会稳定。因此，应急决策问题受到广泛关注。

The author first introduced the research in this article that was rejected: In recent years, major public safety emergencies have frequently occurred in my country, such as vaccine cases, explosion accidents, shipwreck accidents and the new crown epidemic, causing serious losses and threatening social stability. Therefore, emergency decision-making issues have attracted widespread attention.

（二）研究现状（Current research status）

接着作者提到目前国内外尚无通用的应急决策模型，现有研究主要基于多属性决策、大群体决策、案例推理和博弈论等方法。特大突发事件的应急决策被视为复杂多属性群体决策问题，决策属性的确定对决策效果至关重要。现有方法包括信息熵优化、非线性规划、专家判断赋权等，但在突发事件的高不确定性环境下，这些方法的适用性有限。

Then the author mentioned that there is currently no common emergency decision-making model at home and abroad. The existing research is mainly based on methods such as multi-attribute decision-making, large-group decision-making, case reasoning and game theory. Emergency decisions for major emergencies are regarded as complex multi-attribute group decision-making issues, and the determination of decision-making attributes is crucial to the decision-making effect. Existing methods include information entropy optimization, nonlinear planning, expert judgment empowerment, etc., but in the high uncertainty environment of emergencies, these methods have limited applicability.

研究表明，社交媒体平台凭借开放性和实时性，为集结群体智慧提供支持。公众既是突发事件的亲历者，也是重要利益相关方，其社会诉求具有重要的应急管理价值。借助大数据挖掘群智知识，有助于提升应急决策的科学性，因此整合社交媒体数据以汇聚群体智慧成为必然选择。

Research shows that social media platforms provide support for gathering group intelligence with openness and real-time nature. The public is not only a witness to emergencies, but also an important stakeholder, and its social demands have important emergency management value. Using big data to mine group intelligence knowledge will help improve the scientific nature of emergency decision-making, so integrating social media data to gather group intelligence has become an inevitable choice.

（三）局限性（limitation）

社会网络分析与人工智能技术的发展为突发事件期间的群体智慧集结与应急管理提供了支持。政府应急决策正从“闭门决策”向“数据驱动智能决策”转变，学者们利用行为大数据和群体智慧开展研究，如分析公众关注主题演变、监测实时情感变化、提取决策参数等。然而，现有方法仍存在局限性，包括：对数据价值分析不足，容易受虚假信息影响；忽视决策专家观点，可能导致参数不符合现实需求；缺乏对公众行为数据来源及传播机理的深入分析。

The development of social network analysis and artificial intelligence technology provides support for group wisdom aggregation and emergency management during emergencies. Government emergency decision-making is shifting from "closed-door decision-making" to "data-driven intelligent decision-making". Scholars use behavioral big data and group wisdom to conduct research, such as analyzing the evolution of public concerns about topics, monitoring real-time emotional changes, and extracting decision parameters. However, existing methods still have limitations, including: insufficient analysis of data value and susceptible to false information; neglecting the views of decision-making experts may lead to the parameters not meeting actual needs; and lack of in-depth analysis of the source and dissemination mechanism of public behavior data.

四、知识补充（Knowledge supplement）

社会网络分析法是一种研究社会结构的方法，主要用于分析个体（节点）之间的关系（边）及其相互作用。它利用数学、图论和统计方法，将社会关系建模为网络，以研究群体内部的联系、信息传播路径、关键个体的影响力等。

Social network analysis method is a method to study social structure, mainly used to analyze the relationships (edges) and their interactions between individuals (nodes). It uses mathematical, graph theory and statistical methods to model social relations into a network to study the connections within the group, the path of information dissemination, the influence of key individuals, etc.

在社会网络分析中，节点代表网络中的个体，如人、组织、国家等，而边表示个体之间的关系，如好友关系、合作关系、交易关系等。网络中的中心性指标用于衡量节点的重要性，例如度中心性表示节点的连接数量，中介中心性表示节点在信息传播中的桥梁作用，接近中心性表示节点到其他节点的平均距离。此外，网络密度衡量网络的紧密程度，社群用于识别网络中紧密联系的子群体。

社会网络分析法广泛应用于多个领域。例如，在社交媒体分析中，可用于研究微博、Facebook、Twitter等平台上的用户影响力、信息传播路径和谣言扩散。在应急管理中，可用于分析灾难或危机期间的信息传播模式、关键决策者及公众情绪。在商业与市场营销中，可帮助识别关键意见领袖（KOL），优化广告投放，并分析消费者行为。此外，该方法还应用于健康传播，用于研究疾病传播路径和健康干预措施的效果，以及犯罪与安全领域，分析犯罪网络和恐怖组织的联系。

Social network analysis method is widely used in many fields. For example, in social media analysis, it can be used to study user influence, information dissemination paths and spread of rumors on platforms such as Weibo, Facebook, and Twitter. In emergency management, it can be used to analyze the patterns of information dissemination, key decision makers and public sentiment during disasters or crises. In business and marketing, it helps identify key opinion leaders (KOLs), optimize advertising, and analyze consumer behavior. In addition, the method is applied to health transmission, to study the effects of disease transmission pathways and health interventions, as well as to the areas of crime and security, and to analyze the links between criminal networks and terrorist organizations.

总体而言，社会网络分析法通过可视化和定量分析个体之间的联系，帮助理解社会系统的结构和动力学，在社交媒体、公共安全、商业决策等领域发挥着重要作用。

Overall, social network analysis methods play an important role in social media, public safety, business decision-making, etc. by visualizing and quantitatively analyzing the connections between individuals, helping to understand the structure and dynamics of social systems.

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