Guanghui Wang

Global climate change, continuous economic development and accelerated urbanization have increased the frequency and complexity of various incidents. Risk assessment is an important means to deal with different crises and incidents. Based on the systematic analysis of the basic connotation, attribute relationship and main contents of risk assessment, this study extends the traditional two-dimensional risk matrix to multi-dimensional risk matrix. On this basis, this study further proposes four comprehensive risk assessment methods, including total ordinal, weighted average, Euclidean distance and two-norm methods. Empirical research was conducted by selecting three types of natural disasters, regional agro-meteorological disasters, geological disasters and forest fires, in 30 related regions in China between 2010 and 2019. The results indicated that compared to the two-dimensional risk matrix, the multi-dimensional risk matrix can intuitively characterise and compare the all-round risk situation of different regions, periods, types and dimensions, which is more helpful for a systematic analysis and risk comparison. All four evaluation methods proposed in this paper proved able to effectively conduct comprehensive regional risk evaluations with consistent results. However, when considering the fitting coefficient between the results obtained by various evaluation methods and the comprehensive evaluation results, it can be found that the accuracy (i.e. fitting coefficient) of Euclidean distance method is significantly higher than that of the other three methods. In the last 10 years, the temporal order of natural disaster risk in China has been more volatile, with Beijing, Shanxi, Tianjin, Hebei, Liaoning, Ningxia, Zhejiang, Shaanxi, Fujian and Gansu experiencing higher volatility in the ranking of natural disaster risk.

The factors influencing the dissemination of public opinion on social media, the main carrier of public opinion, are diverse, complex and changeable. Existing studies of influential factors of public opinion dissemination focus on the information itself and information sources in the dissemination process, failing to consider the comprehensive influence of multidimensional factors, such as information content, sources and channels. This study takes the identification of multidimensional influential factors of social media information dissemination as the research object and comprehensively sorts out the influencing factors of public opinion. To improve the scientific basis and accuracy of the research, multidimensional factors, including information characteristics, dissemination network structure and user-level attributes, are selected to analyze the effect of influential factors in different dimensions on the dissemination of social media public opinion information using econometric models. Three main conclusions of this paper are as follows: (1) The traditional information characteristics (information content) and information source attributes (user-level factor) are not the only key factors affecting information dissemination, while the information channel (network structure) is worth more consideration. (2) Netizens tend to pay more attention to the psychological and emotional attributes of information when forwarding public opinions. The communication mode in which offline social elites enlighten the public no longer exists; whether a user is a network celebrity or lives in the central area no longer significantly affects public opinion dissemination. (3) The higher the total amount of information users release, the more the information would interfere with the public opinion. This is mainly because users with a higher level of activity may release more invalid information about advertising that has nothing to do with public opinion events.