基于微博数据挖掘的突发事件舆情演化分析--以艾尔玛飓风为例
首发时间:2019-07-19
摘要:[目的/意义] 探索突发事件中不同情感微博对信息传播量的影响,进而发现舆情传播的特点和规律,为舆情分析与决策提供依据。[方法/过程]以特定舆情事件的事实文本数据为来源,以细粒度情绪和生命周期理论为指导,设计研究流程,最终实现以微博数据挖掘的突发事件舆情演化分析。[结果/结论]微博舆情演化分析方法能够揭示面向特定事件的微博在突发事件中所对应的微博细粒度情绪、生命周期各阶段的传播性强弱,以及剖析各阶段对应的细粒度情绪演化规律,研判出分布在文字当中有关联性的、代表性的、重要的微博情绪。
For information in English, please click here
Evolution Analysis of Emergency Public Opinion Based on Microblog Data Mining--A Case Study of Hurricane Irma
Abstract:[Objective/Significance] Exploring the impact of different emotional Weibo on the amount of information dissemination in social media and to discover the characteristics and laws of publicopinion transmission, which can provide the basis for publicopinion analysis and decision making. [Method/Process] This study is based on the text data of a true public opinion event. Guided by fine-grained emotions and life cycle theory, the research process is designed to realize the evolution analysis of public opinion in emergencies based on Weibo data mining. [Results/Conclusions] The Weibo public opinion evolution analysis method can reveal the fine-grained emotions of Weibo corresponding to specific events in the emergencies, the propagation strength of each stage of the life cycle, and the fine-grained emotion evolution law corresponding to each stage. The study judged the representative, important and important Weibo emotions distributed in the text.
Keywords: public opinion evolution emergencies life cycle content analysis Information Dissemination
基金:
引用
No.****
动态公开评议
共计0人参与
勘误表
基于微博数据挖掘的突发事件舆情演化分析--以艾尔玛飓风为例
评论
全部评论0/1000