A Survey on Sentiment Analysis by using Machine Learning Methods

被引：0

作者：

Yang, Peng ^{[1
]}

Chen, Yunfang ^{[2
]}

机构：

[1] Nanjing Univ Posts & Telecommun, Dept Internet Things, Nanjing, Jiangsu, Peoples R China

[2] Nanjing Univ Posts & Telecommun, Dept Comp Sci, Nanjing, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC) | 2017年

关键词：

sentiment analysis; machine learning; technologies;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the emergence of Web 2.0 and the development of social media platforms, more and more users are inclined to share their own opinions with others freely on the Internet. Facing a large number of unstructured comments from social platforms, it is urgent to analyze and judge the tendency of emotion expressed in the text by Natural Language Processing. In this paper, the machine learning methods of sentiment analysis are described in detail. This paper introduces the popular sentiment analysis techniques from the perspective of machine learning technologies, including Support Vector Machine method, Naive Bayes method, Maximum Entropy method and Artificial Neural Network method. Finally, the evaluation methods and challenges are given.

引用

页码：117 / 121

页数：5

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