The suddenness, urgency and social publicity of emergency events lead to great impacts on public life. The deep analysis of emergency events can provide detailed and comprehensive information for the public to get trends of events timely. With the development of social media, users prefer to express opinions on emergency events online. Thus, massive public opinion information of emergencies has been generated. Hence, this paper aims to conduct multidimensional mining on emergency events based on user-generated contents, so as to obtain finer-grained results.,This paper conducted public opinion analysis via fine-grained mining. Specifically, public opinion about an emergency event was collected as experimental data. Secondly, opinion mining was conducted to get users’ opinion polarities. Meanwhile, users’ information was analysed to identify impacts of users’ characteristics on public opinion.,The experimental results indicate that public opinion is mainly negative in emergencies. Meanwhile, users in developed regions are more active in expressing opinions. In addition, male users, especially male users with high influence, are more rational in public opinion expression.,To the best of the authors’ knowledge, this is the first research to identify public opinion in emergency events from multiple dimensions, which can get in-detail differences of users’ online expression.

中文翻译：

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突发事件舆情多维挖掘

突发事件的突发性、紧迫性和社会公开性，给公众生活带来了很大的影响。对突发事件的深度分析，可以为公众提供详细、全面的信息，及时掌握事件动态。随着社交媒体的发展，用户更愿意在网上发表对紧急事件的看法。从而产生了海量的突发事件舆情信息。因此，本文旨在基于用户生成的内容对突发事件进行多维挖掘，以获得更细粒度的结果。本文通过细粒度挖掘进行舆情分析。具体而言，收集有关紧急事件的公众意见作为实验数据。其次，进行意见挖掘，得到用户的意见极性。同时，分析用户信息，识别用户特征对舆情的影响。实验结果表明，突发事件中舆情主要是负面的。同时，发达地区的用户表达意见更为积极。另外，男性用户，尤其是影响力大的男性用户，在舆情表达上更加理性。,据作者所知，这是第一次从多个维度识别突发事件中的舆情，可以得到用户在线表达的细节差异。