Sentiment Analysis Model on Weather Related Tweets with Deep Neural Network

被引:15
|
作者
Qian, Jun [1 ]
Niu, Zhendong [1 ]
Shi, Chongyang [1 ]
机构
[1] Beijing Inst Technol, 5 South Zhongguancun St, Beijing, Peoples R China
关键词
sentiment analysis; deep learning; natural language processing;
D O I
10.1145/3195106.3195111
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Weather related tweets are user's comments about daily weather. We can gain useful information about how weather influence people's mood by analyzing them. This is what we called opinion mining in natural language processing field. Traditional opinion mining algorithm use feature engineering to build sentence model, and classifier like naive bayes is used for further classification. However, these feature vectors can sometimes be insufficient to represent the text, and they are manually designed, highly relevant to the problem's background. In this work(1), we propose a method modeling text based on deep learning approach, which can automatically extract text feature. As for word's vector representation, we incorporate linguistic knowledge into word's representation, and use three different word representations in our model. The performance of the sentiment analysis system shows that our method is an efficient way analyzing user's sentiment on weather events.
引用
收藏
页码:31 / 35
页数:5
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