An Efficient Sentiment Mining Approach on Social Media Networks

In today’s competitive environment, there is an essential need to collect and analyze data from social media, news, and other data streams that concern processing of huge amounts of data. A large number of posts, news, and blogs include opinions about product, service, and different issues. To accomplish an upper advantage, it is regularly important to listen and comprehend what individuals are saying in regard to contenders’ item, benefit, and distinctive issues. We proposed a sentiment mining technique for social media analytics to identify influential opinions. Our aim to mine and to compress every one of the people surveys of an item as well as the polarity of subjective topics which isn’t determine combined with opinion mining previously. Proposed task is performed in three steps: Firstly, mining item includes that have been remarked on by clients; secondly, recognize the supposition sentences in each survey and choosing whether every opinion sentence positive or negative or neutral; and finally, we summarize the results based on real datasets.