期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：9
页码：15137
DOI：10.15680/IJIRCCE.2017.0509050
出版社：S&S Publications
摘要：Sentiment Analysis is the widest term which has been adapted in Machine Learning. The word“Sentiment” refers to a person’s view or opinion and analysing the same views is known as Sentiment Analysis. Inmachine learning language it can be defined as one of the data mining technique which identify, extract or filter theuser’s review or surveys. This paper is focusing on the domain of Sentimental Analysis for twitter posts, news, blogand some other text articles. The main objective here is to check whether certain piece of information is positive,negative or neutral. Opinion Mining is one of the similar terms used for Sentimental Analysis because it derives theopinion of the users through their tweets. We cannot deny the fact that sentiment analysis is very complex, especially inSocial Media World due to its huge scope and length. So to identify the sentiments from text there are two differenttechniques i.e. Symbolic technique and Machine technique. Machine techniques are quite easier and fast as compareto Symbolic techniques.
关键词：Opinion Mining; Sentiment Analysis; Feature Based Sentiment Analysis; Social Media
