A survey of Big Data in social media using data mining techniques

Abstract— World’s largest community Facebook’s ‘Like’ button pressed 2.7 billion times every day across the web revealing what people care about, such an impact of social media that internet user average almost spends 2.5 hours daily on liking, chatting, poking, tweeting on social media, which has become vast source of unstructured data. While dealing with big data it’s difficult for traditional databases and architecture to modify, grill and then structure this data, it can lead to many consumer insights which can help to create win-win situations. It has become necessary to find out value from large data sets to show relationships, dependencies as well as to perform predictions of outcomes and behaviors. Big Data has been characterized by 5 Vs – Volume, Velocity, Variety, Veracity and Value. This paper deals with all these 5Vs, features, challenges, future of Big Data in social media arena using data mining algorithms, tools and Hadoop framework for overcoming challenges of Big Data. There are over a billion users of social media network worldwide, many of whom are frequently active and can be connected by means of their smartphone’s and tablets. Social media indeed has become a main communication network in the daily lives of people around the world generating insurmountable data and these big chunks of data are just waiting to be explored. In fact, social media now embodies the leading and biggest source of consumer data which publishes hundreds and thousands of posts about a company’s products or services every day. < final year projects >