Hot Events Detection of Stock Market Based on Time Series Data of Stock and Text Data of Network Public Opinion

With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and enables investors to quickly identify relevant financial events that may lead to stock market volatility. However, in the research of event detection in the financial field, many studies are focused on micro-blog, news and other network text information. Few scholars have studied the characteristics of financial time series data. Considering that in the financial field, the occurrence of an event often affects both the online public opinion space and the real transaction space, so this paper proposes a multi-source heterogeneous information detection method based on stock transaction time series data and online public opinion text data to detect hot events in the stock market. This method uses outlier detection algorithm to extract the time of hot events in stock market based on multi-member fusion. And according to the weight calculation formula of the feature item proposed in this paper, this method calculates the keyword weight of network public opinion information to obtain the core content of hot events in the stock market. Finally, accurate detection of stock market hot events is achieved.

Hierarchical Research on Pragmatic Failures of Apology in Public Events Under the Vision of New Media

Under the new media,the dissemination and the influence of public events are often far more profound than traditional media.Therefore,it has gained a high degree of social attention.We take the apology mistakes in public events as an example,sort out the types and causes of the mistakes into a context,and propose some relevant strategies.

Research on the Dissemination Mechanism and Guiding Tactics of Public Opinion in Catastrophic Event Network

This paper conducts the analysis on the dissemination mechanism and guiding tactics of public opinion in catastrophic event network. Opinion evolution mechanism can be roughly divided into two classes. One is the belief of people based on their neighbors, on the basis of the public opinion is in the social network of acquaintances. Such networks are mostly using cellular automata model for data simulation, the results of numerical simulation are speci？ c to stabilize near the critical value show that the system will reach a critical stable state. The network information collection is the source of network public opinion monitoring its breadth and depth determine the monitoring results for the clear theme of public opinion information collection. Under this basis, this paper proposes the novel idea of making the dissemination mechanism easier. The proposed idea is novel and necessary, the effectiveness is proved via the theoretical analysis.

Dynamic analysis of major public health emergency transmission considering the dual-layer coupling of community–resident complex networks

We construct a dual-layer coupled complex network of communities and residents to represent the interconnected risk transmission network between communities and the disease transmission network among residents. It characterizes the process of infectious disease transmission among residents between communities through the SE2IHR model considering two types of infectors. By depicting a more fine-grained social structure and combining further simulation experiments, the study validates the crucial role of various prevention and control measures implemented by communities as primary executors in controlling the epidemic. Research shows that the geographical boundaries of communities and the social interaction patterns of residents have a significant impact on the spread of the epidemic, where early detection, isolation and treatment strategies at community level are essential for controlling the spread of the epidemic. In addition, the study explores the collaborative governance model and institutional advantages of communities and residents in epidemic prevention and control.

REDISSE in Benin and Lessons Learned for the Management of Public Health Emergencies after Five Years of Implementation

Introduction: Benin was embarked on phase 3 of the REDISSE Benin project (Regional Disease Surveillance Systems Enhancement) which began in 2018. The objectives were in five key components namely, Surveillance and health information;Laboratory capacity building;Emergency preparedness and response;Human resources management for effective disease surveillance and epidemic preparedness;and Institutional Capacity Building, Project Management, Coordination and Advocacy. After five years of implementation, this study aimed at the documentation of lessons learned and best practices. Methods: A descriptive cross-sectional study. Apart from individual semi-structured interviews, a thematic workshops bringing together the project’s main stakeholders recruited on an exhaustive way by component to identify and validate lessons learned, good practices and propose improvement mechanisms to be taken into account by the sector. Criteria were set up and used to validate best practices and lessons learned. Results: A total 54 (Surveillance workshop), 47 (Preparedness & response workshop), 53 (Human Resources workshop), 26 (Laboratories workshop) participated to the thematic workshops, and five interviews. The good practices (33: 9 for animal health, 7 for human health and 17 crosscutting) and lessons learned (10: 3 for animal health and 7 for human health) have been identified and have been the subject, depending on the case, of proposals for improvement or conditions necessary for their maintenance. Discussion: The richness of a project lies not only in the immediate achievement of its results, but also and above all, in its usefulness for similar interventions, whether in the local, regional, national or international context. It is in this context that the REDISSE project has set out to make public the various lessons learned and best practices from the implementation of its activities over a period of some five consecutive years.

The Influence of Significant Public Health Events on Offline Consumption and Its Pathways

In the face of a significant public health event,consumers may either increase their panic buying or decrease their willingness to make purchases.This study focuses on the impact of a significant public health event on offline store sales and consumer consumption,utilizing data from chain convenience stores in Hefei and Wuhu during early 2019 and early 2020 in China.Employing a difference-in-differences model,the study investigates the effect of the significant public health event outbreak on weekly store sales,order numbers,and consumer consumption in terms of product quantities,transaction amount,average amount per order,and transaction frequency.Different from prior literature that finds hoarding behavior of consumers online,the findings of this paper indicate a significant reduction in stores’offline weekly sales and order numbers,as well as consumers’offline weekly consumption across the four dimensions,as a result of the significant public health event outbreak.Additionally,employing a mediation model,the study explores the pathway of population mobility through which the significant public health event adversely affects offline consumption.Furthermore,subset analysis is conducted for stores located in different areas and consumers with varying characteristics,revealing that the aforementioned conclusions predominantly apply to stores situated in office areas and residential areas,as well as consumers with either no apparent preference for different product categories or a noticeable preference for food.

A Study on the Evolution of Mechanism of Infectious Disease Analysis Model of Event Using Micro-Blog Platform

After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group events to upgrade and expand the scope of harm. It is difficult to deal. So public opinion control is very important. In this paper, we establish an influence model for spreading of public opinion based on SIR model. Through the political analysis, this paper finds that the network group events will subside, but the influence scope, time and ability of event cannot be ignored. As a result of this study, the corresponding strategies are put forward in this paper.

Urban Public Space Development in Harbin Driven by Music Culture Intervention

"Social event driving" has become a way to promote urban development, create urban public spaces and create a city image. As one of the important big cities in northeastern China, Harbin enjoys the reputation of "The Music City", and its public space development is inextricably linked with the driving of music culture. This paper started with the analysis of the correlation between the development of urban public spaces and the development of music culture in Harbin, and studied the influence and driving role of music culture on the construction and development of urban public spaces.

Business Process Analysis and Simulation: The Contact Center of a Public Health and Social Information Office

This article proposes a framework, called BP-M* which includes: 1) a methodology to analyze, engineer, restructure and implement business processes, and 2) a process model that extends the process diagram with the specification of resources that execute the process activities, allocation policies, schedules, times of activities, management of queues in input to the activities and workloads so that the same model can be simulated by a discrete event simulator. The BP-M* framework has been applied to a real case study, a public Contact Center which provides different typologies of answers to users’ requests. The simulation allows to study different system operating scenarios (“What-If” analysis) providing useful information for analysts to evaluate restructuring actions.

Application of Multi-relational Data Clustering Algorithm in Internet Public Opinion Pre-warning on Emergent

At present, there are some resistible illegal operations aiming at creating false public opinions in internet public opinions on emergent event, which seriously disrupted the normal Internet order. However, the traditional research method of internet public opinion pre-waming mainly relies on manual analysis, which is too inefficient to adapt to the analysis of massive internet public opinion information. According to the above analysis, this paper puts forward an internet public opinion pre-warning mechanism on emergent event based on multi-relational data clustering algorithm, discusses the specific pre-waming from the aspects of the state and dissemination of internet public opinions and the historical data, and automatically classifies the internet public opinions through multi-relational data clustering algorithm. And the results show that such method can be used to effectively study the internet public opinion pre-waming on emergent event, with the accuracy rate of as high as 95%.

Analysis of CDC’s Role in Public Health Emergencies

Objective:To explore the role of the Centers for Disease Control and Prevention(CDC)in public health emergencies.Methods:The details of 12 public health events that occurred between January 2021 to December 2022 were analyzed to explore the roles of the CDC.Results:There were 160 patients involved in 10 public health events in 2021 and 48 patients involved in 2 public health events in 2022.Besides,the proportion of school public health events in 2022 was 0%,which was lower than in 2021,which was 80%(P<0.05).99.38%of patients during public health events were sent to the hospital promptly in 2022,which was higher than that in 2021,which was 81.25%(P<0.05).Furthermore,the average time taken for the CDC to control public health events in 2022 was 20.11±1.62 hours,and the average time taken to send inspection reports was shorter than that in 2021.The public satisfaction score was also higher in 2022 compared to 2021(P<0.05).Conclusion:The role of the CDC is to control infectious diseases.Therefore,it is important to pinpoint the existing problems in the strategies implemented by the CDC so that more improvements can be made to better prevent infectious diseases.

中国乡村体育赛事治理的互动机制与模式创新—基于价值治理分析框架

凝聚共同体精神、价值认同和道德规范是实现体育治理现代化、柔性化的重要方式。将多元治理主体的地位和属性这一重要常量纳入乡村体育赛事治理体系进行考察,从乡村体育共同体价值观念整合的视角,回应乡村体育赛事举办中广泛存在的超经济行为逻辑。认为:价值治理应遵循责任认知的价值规范、相互信任的价值理念和“以村民为中心”的价值本位等基本原则;应从关系结构及其信念伦理、权益结构及其理念互构、规则结构及其评价导向展开对组织结构的考察;在历史维度上,乡村体育赛事经历了从“团结目标”到“争做先锋”再到“热爱驱动”,并迈向“荣誉追求”的价值演变进程;面对融媒体时代复杂的风险治理格局,乡村体育赛事需要科学技术赋能,更需要优化价值驱动机制,吸纳多元价值目标,构建更具开放性、兼容性和共享性的制度系统。

基于优化第三代非支配排序遗传算法的城市应急设施模糊选址

以杭州市上城区2022年全年核酸检测点记录数据为基础,采用优化型第三代非支配排序遗传算法(NSGA3),将杭州市上城区划分为10786个50 m×50 m的人口点,模拟每个人口点去往周边核酸检测这一聚集性应急行为,并进行50000次迭代.将迭代结果进行核密度分析,分别得出基于单设施点的15 min生活圈优化结果、基于双设施点的15 min生活圈优化结果、基于适老化需求修正的设施点优化结果,以及基于单设施点的5 min生活圈优化结果.结果显示,以单设施点的15 min生活圈优化结果为例,在不改变服务能力的前提下,基于优化NSGA3迭代后的核酸检测点网络,将设施平均可达时间从292.44 s优化到了264.62 s.基于核酸检测这一行为结果形成城市应急设施的模糊选址范围,得出“小集聚-大分散”空间规律;在此基础上将模糊选址范围转化为“社区级多功能应急空间”,为将来发生应急事件,进行临时应急设施选点决策时提供理论建议.

基于区块链技术的体育热点事件中的网络情绪治理

5G时代下体育网络情绪传播业态发生巨大变革,为其治理带来了新的挑战。当前,体育网络情绪传播主体和范围不断拓展、传播速度不断加快、传播不确性不断增加,使体育网络情绪治理难度不断提高。区块链技术凭借其去中心化、难以篡改、公开透明等优势,不仅可以有效提升体育网络情绪治理的精准性,而且可以有效提升治理效率。基于区块链技术从不同层面构建体育网络情绪治理机制,在宏观层面构建体育网络情绪信息联合治理平台,在中观层面建立基于大数据的体育网络情绪监测体系,在微观层面自媒体及其服务商实时跟踪处理体育网络情绪,以加强体育舆论引导,促进体育事业健康发展。

网络舆情事件链演化分析

为防范舆情风险,分析网络舆情的细粒度演化,提出一种去冗余的衍生事件内容关联演化分析框架。通过文本挖掘技术从海量文本流中提取主要的衍生事件,将舆情内容压缩到人工可判读的数量级;利用词移距计算相邻两个时间片上的衍生事件相似度,构建反映演化关系的衍生事件链图。以“上海特斯拉自燃”事件为例进行事件链演化分析,得到微博网络舆情事件发展不同阶段涉事主体在各个衍生事件中的话题转移关系,最后鲁棒性分析的结果验证了该分析方法具有降低微博短文本冗余信息的能力,提高了事件演化关联识别分析的准确性。该研究方法为舆情事件的事后复盘、同类舆情事件的预判和介入、衍生事件的科学研判提供了决策支持。

护理人员应对突发公共卫生事件心理健康状况影响因素分析

目的调查临床一线护士应对突发公共卫生事件心理健康状况及其影响因素,为提升护士心理健康提供理论依据。方法于2020年2月采用便利抽样法选取某市四所医院中(包括所有定点医院及三级综合医院)工作在发热门诊及隔离病房的192名一线护士作为研究对象。采用一般资料调查表、一般心理健康状况问卷(GHQ-12)、护士职业获益感量表进行调查。结果本次调查中有51.04%(98/192)的一线护士GHQ-12得分≥3分,疑似有心理健康问题。护士职业获益感得分为(44.25±9.90)分。Logistic多因素回归分析结果显示:工作时长、有类似灾害救护经历、护士职业获益感是一线护士心理健康状况的主要影响因素(P<0.05)。结论突发公共卫生事件期间,临床一线护士心理健康问题较为普遍,提高护士职业获益感有利于减少心理问题,管理者需要针对主要影响因素进行干预,改善此类人群心理健康状况。

旅游者风险感知对目的地信任影响研究——政府信任的中介作用

旅游者风险感知与信任密切相关,各种风险所带来的不确定性会改变社会互动并造成信任危机,而旅游者目的地信任是影响旅游者满意度与忠诚度的重要因素。以安东尼·吉登斯关于风险感知和信任的论述为理论依据建立分析框架,通过网络问卷对326名风险经历者进行调查,并以政府信任为中介变量,以风险沟通、应急处置为调节变量,重点探讨了公共卫生事件情境下旅游者风险感知对其目的地信任的作用机制与效应。结果显示:风险感知对旅游者政府信任具有显著负向影响,而风险感知对旅游者目的地信任无显著影响;政府信任对旅游者目的地信任具有显著正向影响;风险沟通在风险感知与政府信任中不存在调节作用,应急处置在风险感知与政府信任中存在调节作用。

一种干扰系数自探测的网络事件选取方法

网络事件在传播过程中会产生相互影响,对这种事件间的影响进行研究有助于深入了解网络舆情的传播规律,并依此采取正确的应对办法.针对不同事件间存在不同干扰效果这一问题,提出了一种干扰系数自探测的网络事件选取方法.该方法使用具有多事件容量特征的mSIR-CA(MultipleSIR-Cellular Automata)模型为推演核心,并借助真实事件数据进行有针对性的参数寻优,使得方法能够根据目标事件,从当前同处于扩散过程的多个备选干扰事件中,进行有效事件选取及干扰效果排序.实验结果表明,根据真实事件训练集对方法参数寻优后,通过对已发生事件标记的事件组进行验证,该方法在有效干扰事件的分类判断、干扰效果排序结果方面有较好的准确率.

基于感知公平理论的公共危机事件后政府信任修复研究

从公平视角探讨政府信任修复的机理,对于危机管理和信任修复领域具有重要的理论和现实意义。本文基于感知公平理论和归因理论构建了政府信任修复模型,分析了公共危机事件后公众感知公平、危机事件归因对政府信任修复的作用机理,并采用情景实验法进行实证检验,研究发现:(1)结果公平、程序公平、互动公平修复策略能有效地修复政府信任;(2)三种公平修复策略对于政府认知信任维度和情感信任维度的修复效果存在显著差异;(3)政府对危机事件的责任归属、稳定性归因会影响三种公平修复策略的修复效果。公共危机事件后,政府可以根据信任受损的维度及事件归因选择适当的公平修复策略。