A Causality Analysis of Societal Risk Perception and Stock Market Volatility in China

Modern China is undergoing a variety of social conflicts as the arrival of new era with the transformation of the principal contradiction. Then monitoring the society stable is a huge workload. Online societal risk perception is acquired by mapping on-line public concerns respectively into societal risk events including national security, economy & finance, public morals, daily life, social stability, government management, and resources & environment, and then provides one kind of measurement toward the society state. Obviously, stable and harmonious social situations are the basic guarantee for the healthy development of the stock market. Thus we concern whether the variations of the societal risk are related to stock market volatility. We study their relationships by two steps, first the relationships between search trends and societal risk perception; next the relationships between societal risk perception and stock volatility. The weekend and holiday effects in China stock market are taken into consideration. Three different econometric methods are explored to observe the impacts of variations of societal risk on Shanghai Composite Index and Shenzhen Composite Index. 3 major findings are addressed. Firstly, there exist causal relations between Baidu Index and societal risk perception. Secondly, the perception of finance & economy, social stability, and government management has distinguishing effects on the volatility of both Shanghai Composite Index and Shenzhen Composite Index. Thirdly, the weekend and holiday effects of societal risk perception on the stock market are verified. The research demonstrates that capturing societal risk based on on-line public concerns is feasible and meaningful.     

基于百度热搜新闻词的社会风险事件5W提取研究

当今中国处于经济转型升级的关键时期,社会主要矛盾发生了历史性变化,社会风险事件发生的频率比以往更高,危害社会稳定.将公众在线的搜索和关注数据映射为潜在的社会风险事件,如何有效地自动标注风险事件以及直观、清晰地描述社会风险事件是本文关注的重点.本文尝试定义风险事件的5W框架来结构化的描述社会风险,包括地点(where)、时间(when)、人物(who)、原因(why)和发生内容(what).风险事件的5W抽取可转化为不同的机器学习任务,包括命名实体识别、风险分类以及关键词抽取.依据5W的抽取任务进而探索有效的抽取方法.通过对风险事件5W的自动抽取,将现实中社会风险这种wicked问题转化为结构化问题进行分析,为研究社会风险提供一个新的视角,对政府部门进行舆情分析与风险监测具有重要意义.     

和谐社会秩序形成机制的系统分析：和谐管理理论的启示和价值

良性健康社会秩序的建立与形成是树立、落实科学发展观及构建社会主义和谐社会的重要目标之一.在系统回顾社会秩序及其构建途径相关理论与实践的基础上,深入地考察了和谐管理理论对建立、形成和谐社会秩序这一发展主题的系统性启示及其价值,并以该理论作为指导思想及分析工具,运用系统工程视角,从政府设计规划职能的优化与完善、环境诱导下社会系统的自主演化以及二者围绕发展主题的有机整合等三个方面对和谐社会秩序的形成机制进行了系统的构建,从而探索出一条基于和谐管理理论的和谐社会中预期的人造秩序、演化的增长秩序乃至最终完整秩序的实现路径.     

The distributed representation for societal risk classification toward BBS posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.     

Ensemble of multiple kNN classifiers for societal risk classification

Societal risk classification is a fundamental and complex issue for societal risk perception. To conduct societal risk classification, Tianya Forum posts are selected as the data source, and four kinds of representations: string representation, term-frequency representation, TF-IDF representation and the distributed representation of BBS posts are applied. Using edit distance or cosine similarity as distance metric, four k-Nearest Neighbor (kNN) classifiers based on different representations are developed and compared. Owing to the priority of word order and semantic extraction of the neural network model Paragraph Vector, kNN based on the distributed representation generated by Paragraph Vector (kNN-PV) shows effectiveness for societal risk classification. Furthermore, to improve the performance of societal risk classification, through different weights, kNN-PV is combined with other three kNN classifiers as an ensemble model. Through brute force grid search method, the optimal weights are assigned to different kNN classifiers. Compared with kNN-PV, the experimental results reveal that Macro-F of the ensemble method is significantly improved for societal risk classification.     

Topics and trends of the on-line public concerns based on Tianya forum

Many social events spread fast through the Internet and arouse wide community discussions. Those on-line public opinions emerge into diverse topics along the time. Moreover, the strength of the topics is fluctuating. How to catch both primary topics and trend of topics over the shifting on-line discussions are not only of theoretical importance for scientific research, but also of practical importance for societal management especially in current China. To try the cutting-edge text analytic technologies to deal with unstructured on-line public opinions and provide support for social problem-solving in the big data era is worth an endeavour. This paper applies dynamic topic model （DTM） to explore the changing topics of new posts collected from Tianya Zatan Board of Tianya Club, the most influential Chinese BBS in mainland China. By analysis of the hot and cold terms trends, we catch the topics shift of main on-line concerns with illustrations of topics of school bus and environment in December of 2011. An algorithm is proposed to compute the strength fluctuation of each topic. With visualized analysis of the respective main topics in several months of 2012, some patterns of the topics fluctuation on the board are summarized.     

基于标准差修正G1组合赋权的人的全面发展评价模型及实证

根据"坚持以人为本, 树立全面、协调、可持续的发展观, 促进经济社会和人的全面发展"的科学发展观内涵, 从生活质量、人口素质、经济发展环境、社会发展环境、人力资本环境和生态环境6个准则筛选国民幸福指数、基尼系数等31个指标构建了人的全面发展评价指标体系. 通过标准差修正的G1 法(序关系分析法)对指标体系进行组合赋权, 建立了基于标准差修正G1组合赋权的人的全面发展评价模型, 并对我国2001-2007的人的全面发展进行评价. 本文的创新与特色一是通过生活质量、人口素质和生态环境等6方面的评价, 反映了和谐社会人与社会和谐、人与自然和谐、人与人和谐的基本要求, 体现了以人为本的科学发展观. 二是通过标准差修正G1组合赋权方法确定指标权重, 使得组合权重体现专家意见和指标数据信息, 避免了在主观赋权中指标重要性标度的给出人为主观确定, 缺少客观依据的问题, 避免了主客观权重分配的问题.     

论和谐社会的系统特征

“和谐”总是系统的一种特征，事物内部各要素之间相互作用是“和谐”的实质内容；研究“和谐社会”，必须坚持辩证唯物主义的基本观点，以科学的社会结构理论为指导，运用现代系统科学的整体性方法、定量分析方法等，也要注意运用电子计算机等现代科学手段；“和谐社会”，是内部结构合理，人、社会、自然相互统一，社会性资源兼容共生的社会。     

基于差异协同原理的和谐社会构建——用协同论构建和谐社会的思考

差异协同论指出,任何一个系统内部的结合能力都来自系统内部各个元素之间差异性相互作用下的协同。我们要构建的社会主义和谐社会,从其本质内涵来看就是一个具有系统质的差异协同体。和谐社会就是社会诸要素协同发展基础上的和谐,即是协同中的和谐;和谐社会就是社会诸要素保持差异与和谐之间的平衡基础上的和谐,即是差异中的和谐。因此,社会主义和谐社会,是一个全面系统的和谐,是差异、协同的辨证统一。     

构建和谐社会离不开系统思维的指导

构建和谐社会,已成为当代社会共识。社会主义和谐社会不仅是我们所追求的社会价值目标、同时也是一种现实的社会构建运动,因而也具有社会实践的本体论意义。社会主义和谐社会具有自身社会运动的系统特征,它本质上是一种系统思维的社会实践诠释。构建社会主义和谐社会,需要系统思维方式的指导,即在构建社会主义和谐社会活动过程中必须贯彻系统思维的开放性原则、整体性原则、复杂性原则和能动调控的实践性原则。     

两型社会市民生活满意度评价指数模型实证研究

建设资源节约型、环境友好型社会是长株潭城市圈生态文明建设的集中体现,也是实现社会文明、和谐发展的必由之路.然而从目前来看,国内对于"两型社会"建设水平的评价,较少从市民生活满意度的角度进行研究.基于此,论文将顾客满意度引入到两型社会建设水平的测评中.论文在分析SCSB(瑞典顾客满意指数),ACSI(美国顾客满意指数)和ECSI(欧洲顾客满意指数)的基础上,建立了两型社会市民生活满意度指数模型.并运用结构方程模型(SEM)估计技术中的偏最小二乘(PLS)路径分析方法对指数模型中潜在变量之间以及潜在变量与可测变量之间的关系进行了检验.最后通过实证研究表明本文所建立的两型社会市民生活满意度指数模型拟合得较好,并根据各变量之间的相关系数为政府提出了相关政策建议.     

Generating Storyline with Societal Risk from Tianya Club

Major societal problems affect the social stability. It is necessary to understand the public opinion toward those issues to avoid social conflicts. Nowadays the social media become the major platform to track what the public is concerned about and which may be of the societal risk. However,it is very tough to capture the public attention in short time due to huge flow of user-generated contents.In this paper, we approach this problem by expanding the method of generating storyline with the result displayed by a multi-view graph. One real-world example is illustrated and evaluation is given to show the effectiveness of the proposed method.     

基于信息不对称的银行信贷风险决策机制及分析(Ⅰ)——信贷风险决策模型

研究商业银行在信息不对称的信货市场中 ,当存在高、低两种不同风险类型的贷款企业时 ,银行因无法准确判断企业投资项目的风险类型 ,因而造成了信贷资金的损失或机会损失 .分析并研究了这两种损失常见的几种情形及其数学原理 ,建立了银行信贷风险的决策模型 ,给出其 Kuhn-Tucker条件 .指出了在模型之下 ,当抵押品作为鉴别企业风险类型的手段失效时 ,为规避信贷风险 ,银行对企业提供的抵押品价值将有特殊的要求 .     

消费品生命周期隐患识别与风险评价的三维矩阵方法

面对近年我国产品质量安全事故频发、消费者人身安全与健康遭受不同程度的威胁以及出口产品不时被召回或退回的问题，给出了一种基于消费品生命周期和事故致因的隐患识别及表征方法，有助于提升人们对消费品危害规律的认知水平并为消费品风险评价奠定基础. 考虑到事故伤害受体的能力和行为会对消费品缺陷或隐患演化及事故伤害后果产生重要影响，在常规风险评价二维矩阵的基础上，加入风险受体的脆弱性要素，提出了消费品风险评价的三维矩阵方法，能够更好地表征消费者能力与行为等主观要素对消费品隐患事故及危害的影响作用. 以家用电器风险评价为例，基于欧盟非食品类消费品快速预警系统（RAPEX）对中国消费品通报信息分析和专家评价打分，形成了消费品评价三维风险矩阵，分析了家用电器的风险规律，为消费品的风险评价提供了新思路、新方法.     

事物系统与和谐统一——关于进步发展问题的现实性探讨

和谐统一是构成真正系统的前提，也是系统得以进步发展的根据。社会真正的发展需要和谐，可持续和全面的发展更加需要和谐。和谐统一的关系不仅是利益平衡及平等互换的顺畅通道，而且是公正平等的象征，更是正义、博爱、民主和自由的发源地。简言之，和谐统一是实实在在的客观理性和社会可持续全面发展必须严格遵循的客观规律。     

An Empirical Feasibility Study of Societal Risk Classification Toward BBS Posts

Societal risk classification is the fundamental issue for online societal risk monitoring. To show the challenge and feasibility of societal risk classification toward BBS posts, an empirical analysis is implemented in this paper. Through effectiveness analysis, Support Vector Machine based on Bag-Of-Words (BOW-SVM) is adopted for challenge validation, and the distributed document embeddings of BBS posts generated by Paragraph Vector are applied to feasibility study. Based on BOW-SVM, cross-validations of BBS posts labeled by different groups and annotators are conducted. The big fluctuation of cross-validation results indicates the differences of individual risk perceptions, which brings more challenges to societal risk classification. Furthermore, based on the distributed document embeddings of BBS posts, the pairwise similarities of more than 300 thousands BBS posts from different societal risk categories are compared. The higher similarities of BBS posts in the same societal risk category reveal that BBS posts in the same societal risk category share more features than BBS posts in different categories, which manifests the feasibility of societal risk classification of BBS posts, and also reflects the possibility to improve the performance of societal risk monitoring.     

系统辩证学与和谐社会的构建及管理

以差异协同律为核心的系统辩证学为和谐社会的构建和管理提供了一种新的理论视角,它扬弃了哲学对和谐的理解,把整体、秩序、协同作为构建和管理和谐社会的要素。管理科学要有效地处理复杂环境中涌现出来的不确定性,就应将系统辩证学作为管理和谐社会的一种理论指南。     

社会主义和谐社会系统的层面观

社会主义和谐社会是一个复杂的动态的机制系统,对社会主义和谐社会的研究,往往是从实现民主政治、经济与生态、人与社会等纵向方面加以论述,是一种用正确设想来设计发展过程的方法。基于逻辑上完善性和科学性,我们应把社会主义和谐社会系统横向分解成发展层面,并在实施过程中加以考查。从构建社会主义和谐社会的过程看,层面系统包括理论层、机制层和实践层三个层面,理论层是社会主义和谐社会的先导,机制层是社会主义和谐社会实现的制度设计,实践层是社会主义和谐社会顺利进行的保障。     

论环境在构建和谐社会中的作用——系统学视角下的和谐社会途径

和谐社会是一个整体优化的社会系统，是人与人、人与社会、人与自然和谐发展的体系。从系统与环境关系的视角，生态良好的自然环境、安定有序的社会环境、和睦共赢的国际环境是我国构建社会主义和谐社会的前提和基础。     

Social Entropy Theory: An overview

Social Entropy Theory (SET) is a very general macrosociological systems theory. The present paper is an overview which presents selected salient features of the larger model. Special attention is given to the specification of macrosociological variables which can serve as social indicators in a comparative framework of societal development. First, the goals of the SET model are stated. Then the basic model is sketched, and entropy is discussed as a measure of system state. Attention then turns to the specification of a holistic set of macrosociological systems variables. By seeking all correlates of the level (L), six salient global components are developed. These are population (P), information (I), spatial area (S), technology (T), organization (O), and level of living (L). This PISTOL (or PILOTS) model seems to be exhaustive and forms a comparative framework (when suitable indicators are specified for all components) for the analysis of social systems at all levels of development. A distinction is made among global, mutable, and immutable properties.