基于大规模弹幕数据监听和情感分类的舆情分析模型  

A public opinion analysis model based on Danmu data monitoring and sentiment classification

作　　者：叶健 赵慧 YE Jian;ZHAO Hui(School of Computer Science and Software Engineering,East China Normal University,Shanghai 200062,China)

机构地区：[1]华东师范大学计算机科学与软件工程学院

出　　处：《华东师范大学学报（自然科学版）》2019年第3期86-100,共15页Journal of East China Normal University(Natural Science)

摘　　要：随着在线视频平台的快速发展,弹幕逐渐成为人们表达观点的一个重要途径,尤其受到年轻人的欢迎.与常规的文本不同,弹幕文本普遍较短,表达随意,网络词汇较多,一些常规的停用词被用于表达情感.提出了一种基于弹幕数据的舆情分析模型,针对弹幕数据生成和存储特点,提出了热点检测循环自适应弹幕数据获取算法;扩充了情感词典来区分弹幕中情感倾向数据和中性数据,以解决弹幕中出现的网络词汇较多的问题;基于卷积神经网络(Convolutional Neural Network,CNN)建立了情感褒贬分类模型,用来区分情感倾向弹幕的正负情感倾向,在此基础上得到了舆情分析的结果.实验表明,本文的舆情分析模型能有效地表达新闻类弹幕数据的舆情分析结果.With the rapid development of online video platforms,Danmu has gradually become an important way for people to express their opinions,and it is particularly welcomed by young people.Unlike conventional texts,Danmu texts are generally short,unstructured,and involve Internet slang as well as conventional stop words to express emotions.In this paper,a public opinion analysis model based on Danmu data is proposed.According to the data generation and storage characteristics of Danmu,a hotspot detection-based loop algorithm is proposed for Danmu data collection.Moreover,the sentiment dictionary to distinguish emotional tendencies is expanded to include network vocabularies commonly appearing in Danmu.Finally,based on the convolutional neural network(CNN),we build a classification model to distinguish positive and negative emotions.Experiments show that the public opinion analysis model of this paper can effectively demonstrate public opinion analysis of Danmu data.

关 键 词：弹幕情感 网络舆情 情感分类 深度学习 网络爬虫 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]