• Prinkle Vilas Shete
• Rohan Vijay Gokhale
• Sanket Hanmant Masudge
• Maya P. Shelke

Knowing and understanding the nature of market is difficult task and requires thorough study regarding the context. One of the easiest way is to consider public opinion regarding the market situation to understand the ups and downs in the sector. This paper considers public sentiments along with news related with the market condition to predict the nature of market. Our work consists of data collection from twitter and various news sites to generate overall sentiment regarding the market and with the help of that finding the correlation between market price and sentiments to train our models for prediction. To further improve accuracy of prediction, the proposed approach considered ensemble learning method in which it trained more than one model and generated the poll among them to precise results

Tweets; Sentiment Analysis; Ensemble Learning; Opinion Mining; Website Scrapping; Machine Learning

"Market Prediction using Sentiment Analysis on Real Time Data Streams", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.35-38, May-2019, Available :http://www.jetir.org/papers/JETIRBO06005.pdf

"Market Prediction using Sentiment Analysis on Real Time Data Streams", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp35-38, May-2019, Available at : http://www.jetir.org/papers/JETIRBO06005.pdf