大数据环境下面向事故灾难类的突发事件舆情引导事例分析

Case Analysis on the Public Opinion Guidance for Accident Disasters under the Environment of Big Data

大数据环境下,基于突发公共事件产生的社会自媒体数据呈现出数据量大、结构复杂、类型多样等特征,政府的舆情引导对公共事件网民情绪的趋势发展至关重要。本文以事故灾难类微博数据为基础,以"天津港爆炸事件"为研究对象,首先利用爬虫工具收集微博内容,然后通过ROST CM内容挖掘软件进行中文词频分析,最后通过SPSS对微博情感进行分析统计。研究发现,公众情绪容易受到集群效应的影响,网民群体情绪的不稳定性会导致其行动的不确定性,政府或意见领袖的积极引导将会促进突发事件的良性发展。本文的研究将有助于政府有关部门了解突发公共事件的传播状况并做出快速反应,并提升政府对网络舆情的监控能力与监控水平。

Under the big data environment, the data of social media caused by emergent public events has large amount of data,complex structure, various types, and so on. The effect of government＇s public opinion guidance on the development trend of Internet users＇ mood of public events is very important. Based on the micro-blog data of accident disaster, this paper takes ＂explosion of Tianjin Port＂ as the object of study to collect micro-blog content by the crawler tool, then, analyze the Chinese frequency by ROST CM content mining software and finally analyze and count the micro-blog emotion by SPSS. The study found that the public sentiment is easily affected by the cluster effect, the uncertainty of Internet users＇ mood will lead to the uncertainty of their action, the positive guidance of the government or the opinion leaders will promote the positive development of the emergency. The research helps the government departments to understand the situation of public emergencies and make a quick response, and enhances the ability of the government to monitor the network public opinion and the level of monitoring.