• S. Gandhimathi
• Dr. V. Baby Deepa

The biggest challenging issue of data analysis concept is expressly bulky volume of data. Another big issue of big data is becoming the rapid function to solving it in an efficient manner. In recent years, SMN (Social Media Networks) is generating a huge tone of data that includes structured, semi-structured and unstructured data. The data which is mentioned in different formats such as audio, video, text, numbers, hash tag and URLs. Accordingly, the data require be analyzing and extracting from the variety regarding big data. Big data contains different analytical techniques. In this paper, the elaborate discussions focus Sentiment Analysis. Sentiment (Opinion) study on big data streams from the continuously generates text streams on SMNs to hundreds of millions of online consumer analysis provides several organizations in all the fields with opportunities to find out valuable intelligence from the enormous user generated text streams. An overview of Sentiment Analysis, various techniques for sentiment analysis and detailed on the various applications and challenges in sentiment analysis is presented.

Big Data, Big Data Analytics, Social Media, Sentiment Analysis, Opinion Mining, Social Media Network (SMN), MapReduce, Apache Hadoop, Social Media Analytics (SMA)

"STUDY ON SENTIMENT ANALYSIS IN BIG DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.402-409, April-2019, Available :http://www.jetir.org/papers/JETIR1904D54.pdf

"STUDY ON SENTIMENT ANALYSIS IN BIG DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp402-409, April-2019, Available at : http://www.jetir.org/papers/JETIR1904D54.pdf