高原科学研究

随着Web2.0技术的发展,社交平台逐渐成为热点事件社会情绪的集散地。准确分析民众的社会情绪是热点事件舆情监管的重要环节。文章积极探索了基于网络文本大数据的热点事件社会情绪分析模型与方法,首先从网络文本大数据获取、数据预处理、社会情绪分类体系、情感词典构建以及社会情绪分类等模块搭建了社会情绪分析模型;其次基于种子情绪词和词汇相似度计算方法实现了情绪词典自动构建方法;再次分别给出了基于情绪词典和文本分类算法的热点事件情绪分析方法;最后在"巴黎圣母院大火"和"任正非访谈实录"两个热点事件真实数据上对文章提出的模型和方法进行了验证,证明了模型和方法的有效性。

With the development of Web 2.0, social platform has gradually become the distribution center of social emotions of hot events. Accurate analysis of social emotions is an important part of public opinion management. This paper actively explores the model and method of social emotional analysis of hot events based on big text data. Firstly, a social emotional analysis model is built based on three modules: big text data acquisition and preprocessing, social emotional classification system, emotional dictionary construction and social emotional classification. Secondly, based on seed emotional words and lexical similarity calculation method, the automatic construction method of emotional dictionary is realized. Thirdly, the emotional analysis methods of hot events based on emotional dictionary and text classification algorithm are presented. Finally, the model and method proposed in this paper are validated on the real data of "Notre Dame Fire in Paris" and "Ren Zhengfei's Interview Record", which prove the validity of the model and method.