| 摘 要: 近年来突发公共事件频出，随着互联网的普及和大数据等信息技术的迅猛发展，Twitter、博客、微博等 使得公众在突发公共事件发生后表达个体情绪更加便捷。本文以“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。 |
| 关键词: 大数据；突发公共事件；情绪；舆情引导 |
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中图分类号: TP312.63
文献标识码: A
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| An Analysis of Micro-Blog Users' Emotions in Public Emergencies Based on Big Data |
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LU Yanxia，WU Di，HUANG Chuanlin
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(Dalian Neusoft University of Information, Department of Information Management, Dalian 116023, China )
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| Abstract: With the development of internet and big data,public emergencies frequently occurred in recent years.The public are more likely to express individual emotional states via Twitter,blog,micro-blog,etc.This paper focuses on the microblog data in the Tianjin Explosion event.Firstly,micro-blog contents are collected through crawler tools.And then,the Chinese word frequencies in the micro-blog contents are analyzed through ROST CM. Finally,the analysis and statistics of the microblog users' emotions are conducted through SPSS.The research results show that public emotions are easily influenced by the clustering effect,the instability of cyber citizens' emotions can lead to the uncertainty in actions,and the active guidance from governments and opinion leaders will promote the healthy development of public emergencies. |
| Keywords: big data;public emergencies;emotion;public opinion guidance |
