EXPLORING ON-LINE SOCIETAL RISK PERCEPTION FOR HARMONIOUS SOCIETY MEASUREMENT

The nearly 30-year economic growth miracle brings the consequent tremendous poor-rich gap leading strong drives for social transformation in current China. Chinese top leaders have realized to increase the peoples＇ income, improve quality of life and construct a ＂harmonious society＂ as key missions especially in recent 10 years. How to measure a harmonious society is one important topic as different measures may lead to different development policies. This paper outlines over 10 indices relevant to measure a harmonious society. Some are global indicators, while some are contributed by domestic researchers and arouse debates. Most of those indicators require conducting surveys on social attitudes under micro levels, which is always time consuming with problem of data quality. As Internet technology advances provide ways to record and disseminate fresh community ideas and thoughts conveniently, detecting topics or emotions from on-line public opinions is becoming a trend or one supplement way to overcome those data acquisition problems. This paper discusses one approach to on-line societal risk perception using hot search words and BBS posts. Such a trial aims to provide another way to societal risk perception different from those in traditional socio psychology studies. Challenges are also indicated.

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.

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.

A CAUSALITY ANALYSIS OF SOCIETAL RISK PERCEPTION AND STOCK MARKET VOLATILITY IN CHINA

Modem China is undergoing a variety of social conflicts as the arrival of new era with thetransformation 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 intosocietal risk events including national security, economy ＆ finance, public morals, daily life, socialstability, government management, and resources ＆ environment, and then provides one kind ofmeasurement toward the society state. Obviously, stable and harmonious social situations are the basicguarantee for the healthy development of the stock market. Thus we concern whether the variations ofthe societal risk are related to stock market volatility. We study their relationships by two steps, firstthe relationships between search trends and societal risk perception; next the relationships betweensocietal risk perception and stock volatility. The weekend and holiday effects in China stock market aretaken into consideration. Three different econometric methods are explored to observe the impacts ofvariations of societal risk on Shanghai Composite Index and Shenzhen Composite Index. 3 majorfindings are addressed. Firstly, there exist causal relations between Baidu Index and societal riskperception. Secondly, the perception of finance ＆ economy, social stability, and governmentmanagement 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.

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.

Evolution Analysis of Societal Risk Events by Risk Maps

Event evolution analysis which provides an effective approach to capture the main context of a story from explosive increased news texts has become the critical basis for many real applications,such as crisis and emergency management and decision making.Especially,the development of societal risk events which may cause some possible harm to society or individuals has been heavily concerned by both the government and the public.In order to capture the evolution and trends of societal risk events,this paper presents an improved algorithm based on the method of information maps.It contains an event-level cluster generation algorithm and an evaluation algorithm.The main work includes:1)Word embedding representation is adopted and event-level clusters are chosen as nodes of the events evolution chains which may comprehensively present the underlying structure of events.Meanwhile,clusters that consist of risk-labeled events enable to illustrate how events evolve along the time with transitions of risks.2)One real-world case,the event of"Chinese Red Cross",is studied and a series of experiments are conducted.3)An evaluation algorithm is proposed on the basis of indicators of map construction without massive human-annotated dataset.Our approach for event evolution analysis automatically generates a visual evolution of societal risk events,displaying a clear and structural picture of events development.

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.

Nuclear Energy and Its History: Past Consequences, Present Inadequacies and a Perspective for Success

An attempt is made to locate nuclear technology within a logical context considering history, risks, societal catastrophes and perspectives: the need is identified for a new direction in the exploitation in order to restore the role in energy production. We depict the situation coming from a marvelous history of discoveries started at the beginning of the XX century;heroes are recalled who made possible something that is inconceivable today: design, construction and production of electricity in a few years;that history was tainted by intentional nuclear explosions, i.e. the original sin that we are now paying. Then, we attempt to show that the societal risk is an inherent part of the civilization. Restoring the public trust (towards nuclear fission technology) by matching nuclear safety with the current technological status and advancers in risk assessment is the key objective. The “independent assessment”, or a principle for the exploitation of nuclear energy already stated in the 50’s of the previous century, shall then re-appear. This is used to erect the signpost for a “dynamic barricade” to further reduce the risk of operation of nuclear reactors and to match the design with current technological capabilities and with the frontiers of the research.