@inproceedings{0732f9ba1a194b3b81ccf301e5bbd6cd,
title = "Emotion monitoring and abnormal warning based on online comments",
abstract = "This article aims to find out and monitor emotion tendency contained in online comments to support decision making. We have constructed an emotion monitoring and abnormal warning model based on sentiment classification. We compared multiple sentiment classification methods for Chinese online comments on training set. Experimental results showed that the performance of information gain feature selection and support vector machine is the best. In the end, we gave an application research on two competitive products of the emotion monitoring and abnormal warning model to identify potential opportunity and risk.",
keywords = "Abnormal warning, Online comment, Sentiment classification, Sentimental indicator",
author = "Hong Li and Jianxin Zhang",
year = "2014",
doi = "10.2495/ISME20131342",
language = "英语",
isbn = "9781845648282",
series = "WIT Transactions on Information and Communication Technologies",
pages = "1045--1052",
booktitle = "Information Science and Management Engineering",
note = "WIT Transactions on Information and Communication Technologies ; Conference date: 07-05-2013 Through 08-05-2013",
}