• Miss. Priyanka V. Chandegaonkar
• Mr. K.V.Reddy

More recently, the Social Media has become extremely popular to share the user’s viewpoints to their friends by using various social networking platforms. It creates obligatory for the users to post their reviews for other users to learn about the quality of the products. But there is much information overloading problems. So to address this problem we propose, A Sentiment Analysis and Features Extraction of Reviews Using Latent Dirichlet Allocation Method used to extract product features, to deal with incorrect sentiment estimation, improve the precision of sentiment mapping, enhance the sentiment dictionary and to calculate the sentiment score and improve prediction accuracy and reliability in the original recommender systems. As the result, it helps to boost the recommendation performance.

Sentiment Analysis, User Sentiment Measurement, Information retrieval, Features Extraction, Sentiment Estimation

"Sentiment Analysis and Features Extraction of Reviews using Latent Dirichlet Allocation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.222-228, November-2018, Available :http://www.jetir.org/papers/JETIR1811932.pdf

"Sentiment Analysis and Features Extraction of Reviews using Latent Dirichlet Allocation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp222-228, November-2018, Available at : http://www.jetir.org/papers/JETIR1811932.pdf