A Quick Emergency Response Model for Micro-blog Public Opinion Crisis Based on Text Sentiment Intensity

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, microblog 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.