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A Quick Emergency Response Model for Microblog Public Opinion Crisis Based on Text Sentiment Intensity

机译：基于文本情感强度的微博舆情危机快速应急响应模型

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摘要

On the basis of discussing the information spreading mechanism under Internet environment, we have studied on how to build a public opinion monitoring model according to the semantic content or text mining in recent years. A micro-blog public opinion corpus named MPO Corpus on the content of micro-blog information as a test data set has been constructed by our research team. In this paper, it proposes a quick emergency response model (QERM) for micro-blog public opinion crisis oriented to Mobile Internet services. Firstly, it describes the micro-blog cases and emergency response plan library using web ontology language (OWL), which makes the transitive logical reason capacity among micro-blog subjects, micro-blog cases and emergency plans. Secondly, it proposes an algorithm to calculate the sentiment intensity of micro-blogs from three levels on words, sentences and documents based on HowNet Knowledge-base respectively. Thirdly, we continue to study on how to update cases under the subjects and quick response processes for micro-blog case base. Finally, we design a test experiment which shows some merits of QERM in time, which basically meets the quick emergency response demand on the micro-blog public opinions crisis under Mobile Internet environment. Thus, it will provide more efficient support to the government and related monitoring departments involved with the public opinions crisis.
机译：在探讨互联网环境下的信息传播机制的基础上，研究了近年来如何根据语义内容或文本挖掘来构建舆论监督模型。我们的研究小组已建立了一个名为MPO语料库的微博客民意语料库，该语料库将微博客信息的内容作为测试数据集。本文针对面向移动互联网服务的微博客舆论危机提出了一种快速应急响应模型（QERM）。首先，利用网络本体语言（OWL）描述了微博案例和应急预案库，使得微博主题，微博案例和应急预案之间具有传递逻辑推理的能力。其次，提出了一种基于知网知识库从单词，句子和文档三个层次分别计算微博情感强度的算法。第三，我们继续研究如何更新微博案例库的主题和快速响应过程下的案例。最后，我们设计了一个测试实验，及时显示了QERM的优点，基本满足了移动互联网环境下微博舆情危机的快速应急需求。因此，它将为参与民意危机的政府和相关监督部门提供更有效的支持。

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