Investigating sentiment analysis using machine learning approach

被引:0
作者
Sankar, H. [1 ]
Subramaniyaswamy, V [1 ]
机构
[1] SASTRA Univ, Sch Comp, Tanjore, Tamil Nadu, India
来源
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SUSTAINABLE SYSTEMS (ICISS 2017) | 2017年
关键词
Sentiment Classification; Natural Language Processing; Supervised Learning; Unsupervised Learning; HWW2V;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Sentiment Analysis is an approach of studying people's emotions and sentiments based on a particular topic, service, event and it attributes. Sentiment analysis appears as a part of various business analysis systems to find opinions about their services or products. Both the availability of CPU resources and enormous amount of data generated by the users makes sentiment analysis an active research field in upcoming years. Most of the existing approaches focus on efficient feature extraction, at the same time some approaches focus on extracting semantic features, which makes mush contribution to sentiment analysis. This review paper gives a comprehensive overview on Sentiment analysis using NLP (Natural Language Processing) techniques. First, we start with some NLP techniques which are generally needed for preprocessing the input data. Second, we introduce various approaches and some problems related to sentiment analysis and discuss some challenges and problem in sentiment analysis. Finally, we illustrate recent trend in sentiment analysis and its related works.
引用
收藏
页码:87 / 92
页数:6
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