文章基本信息

标题：Framework for Sentiment Analysis of Twitter Post
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作者：Rohit Shukla ; Nishchol Mishra
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
卷号：5
期号：3
页码：3426
DOI：10.15680/IJIRSET.2016.0503128
出版社：S&S Publications
摘要：In micro-blogging services like Twitter offers a robust outlet for people’s thoughts and feelings it's acolossal ever-growing provider of texts ranging from everyday observations to concerned discussions. This papercontributes to the sphere of sentiment analysis, that aims to extract emotions and sentiment from text. A basic goal is toclassify text as expressing either positive or negative feeling. Sentiment classifiers are created for social media text likeblog posts, product reviews, and even Tweets. With increasing quality of text sources and topics, it is time to reexaminethe quality sentiment extraction approaches, and presumptively to redefine and enrich the definition ofsentiment.
关键词：language processing; sentiment analysis; opinion mining; social media data mining