基于迁移学习的微博情绪分类研究
关键词 情感分析 情绪分类 迁移学习 微博情绪
毕业论文外文摘要
Title Emotion Classification of Micro-blogging Based on Transfer Learning
Abstract
Weibo allows users to publish their own views and share the new things which contain a wealth of user emotions anytime and anywhere. The classification of the micro blog user emotions can let the enterprise accurately grasp the emotional attitude of the user to the product, but also help the government monitor the public sentiment in time, and maintain social stability. This paper selects the microblog corpus of two different domains in the field of life and the outbreak period of H7N9. The emotional classification of the unlabeled microblog data in the H7N9 outbreak period is carried out with the existing microblog data. Through word segmentation, feature selection, feature weight calculation, migration learning NB, IBK, SOM model and other technologies, subjective and objective classification, emotion classification and sentiment classification are conducted and its accuracy is detected at the same time. The distribution of public opinion in the H7N9 outbreak period is obtained which summmaries negative emotions more than positive emotion. Negative emotions are concentrated in the "anger" and "surprise", but positive emotions "happy" for vaccine successful development are accounted for a large part . It is concluded that, when public health security incident is broken out of, the relevant research should be released to the public in time to stabilize the public mood. At last, this paper summarizes and prospects the shortcomings of the research.
Keywords Emotion Analysis, Emotion Classification, Transfer learning, Micro-blog emotion
目录
1 绪论 1
1.1 研究背景 1
1.2 研究意义 2
1.3 研究思路 2
1.4 组织结构 3
2 相关研究综述 5
2.1 情感分析综述 5
2.1.1 不同情感级别的情感分析 5
2.1.2 情感分析研究流程 6
2.2 微博情绪分类概述 7
2.2.1 微博情绪的特点 7
2.2.2 微博情绪分类方法 7
2.2.3 微博情绪分类研究现状 8
2.3 迁移学习在情感分类中的应用 8
2.3.1 迁移学习定义 8