• Densy David E
• Anver S R

The amount of data in our industry and the world is exploding. Data is being collected and stored at huge rates. The challenge is not only to store and manage the vast volume of data (“Big Data”), but also to analyze and extract meaningful value from it. Big Data comes in many forms. It comes as customer information and transactions contained in customer-relationship management and enterprise resource planning systems, HTML based web stores etc. The information posted on social network and blogging sites including Facebook, Twitter and Youtube mainly constitutes the social media data, which is a form of Big Data. When purchasing a product for the first time one usually needs to choose among several products with similar characteristics. As the companies promote their brands and products by pointing out only good characteristics, the best way to choose the most suitable product is to rely upon the opinions of others.ie., the independent unbiased consumer reviews are known to be the most credible sources of product or service information and people tend to rely primarily on them when making a decision about a purchase. The system collects opinions about an item from the web, evaluate them aggregates these evaluations and offers cumulative, east-to- understand information. Generated information is intended for the possible prospective customer but also for the company managers providing them with additional guidance in future business development.

Big Data, Sentiment Analysis, Hadoop, HDFS, MapReduce, Twitter

"Sentiment Analysis of Social Media Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.1, Issue 7, page no.652-658, December-2014, Available :http://www.jetir.org/papers/JETIR1701A93.pdf

"Sentiment Analysis of Social Media Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.1, Issue 7, page no. pp652-658, December-2014, Available at : http://www.jetir.org/papers/JETIR1701A93.pdf