The detailed work done in developing a system used for opinion analysis of a product or a service. The system readily processes the tweets by pulling data from twitter posts, pre-processing it and connecting it to Twitter API by REST call method and showing it graphically. We have given the analysis for the public tweets by API and filters them for various products , persons and services. For written product reviews, the best solution is video review. Collecting comments from YouTube videos and extracting the exact tone or behavior behind it. The most widely used approaches in opinion mining focus only on tweets or written product reviews available on websites like Amazon. Various emotions that can deal here namely Anger, Anticipation, Disgust, Fear, Joy, Sadness, Surprise, Curiosity, Excitement, Gratitude, Serenity, Hope, Pride, Amusement, Jealousy, Guilt, Discouragement, Frustration, Rejection, Disappointment, Loneliness, Interest, lack of interest, Concern, Sympathy and Calm. Online news is also now trending and extracting the proper tone behind the news. The analysis which is used to classify the sentiment as positive, negative, neutral, strong positive, weak positive, strong negative, and weak negative. The results shown textually and graphically.

Anumula Manjula,Dr. A. Rama Mohan Reddy."Sentiment Analysis on Social media". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084,Vol.6, Issue 11, pp.1-6,November - 2019,

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