• Joseph Philip
• Ann Baby
• A.Kannammal

Opinion mining evaluates people's opinions, sentiments, assessments, outlooks, and feelings from a written language. One of the most dynamic research areas in natural language processing, it is also extensively studied in fields of data mining like web mining and text mining. Opinion mining also finds its vast applications in management sciences and social sciences due to its importance to business and society asa whole. The emergent importance of opinion analysis parallelswithexpansion of socialmedia such as Facebook, Twitter, and social networks. This research suggests a stand-alone platform which enables users to perform opinion analysis which makes use of Twitter API to gather information aboutthe tweets and its users. The proposed model is used to analyse whether the opinion in a text is neutral, positive ornegative. As users tend to post frank and blunt comments in twitter, it has emerged as a platform to check people’s feedback.The inclusion of hashtags to attract social attention also is a trigger for opinion mining. Twitter Search and Streaming APIs with the Stanford NLPlibrary are used to opine the data collected. The pre-processed data passes through the opinion generation phase where opinion classes are defined for polarity. Words are labelled with opinions, and the general opinion of a tweet is thus analysed, in this research paper.

Twitter, Opinion Mining, Opinion Classes.

"THE GOOD, THE BAD AND THE UGLY: OPINION MINING ANALYSIS ON USER TWEETS IN TWITTER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.124-130, May 2019, Available :http://www.jetir.org/papers/JETIRDA06022.pdf

"THE GOOD, THE BAD AND THE UGLY: OPINION MINING ANALYSIS ON USER TWEETS IN TWITTER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp124-130, May 2019, Available at : http://www.jetir.org/papers/JETIRDA06022.pdf