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：2016
卷号：4
期号：3
页码：3184
DOI：10.15680/IJIRCCE.2016.0403045
出版社：S&S Publications
摘要：The importance of Text M ining applications has increased in recent years because of the large number of web - based applications which lead to the creation of such data. Now a days , newer aspects of Text Mining can be apply on emerging platforms such as Social Networks. Opinion Mining and Sentiment Analysis are one of the applications of T ext Mining. Opinion Mining refers to the extraction of lines and phases from the social networks that contain some opinion. Sentiment analysis identifies the polarity of opinion being extracted. Daily huge amount of data is generated by these Social networks such as Twitter. Users not only use these social networks but also give their valuable feedba ck, thus generating additional information. Due large amount of users opinion, views, feedback and suggestion available through social networks, it's very much essential to explore, analyse and organize their views for better decision making. This paper fo cuses on existing approaches for opinion mining on social data especially for twitter data and also modifies techniques for sentiment analysis on social data in order to obtain better result that will helpful to user for better Decision Making
关键词：Microblogging sites;Twitter; Opinion Mining; Sentiment Analysis; MPQA Lexicon; Tree Tagger
