Social opinion mining and concise rendition

To create a sentimental analysis tool for opinion mining of social media data. Information available from social networks is beneficial for analysis of user opinion, for example measuring the feedback on a recently released product, movie or a MOOC, policy change or ongoing events. Using Social network APIs, Python NLTK, automatic collection of a corpus for sentiment analysis and opinion mining purposes is done. Using the corpus we build a sentiment classifier based on Naive Bayes classification that is very accurate, that is able to determine positive, negative and objective sentiments for a document with specificity factor. We also summarize the given input content.