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

被引:0
|
作者
Gole, Sheela [1 ]
Tidke, Bharat [1 ]
机构
[1] Flora Inst Technol, Dept Comp Engn, Pune, Maharashtra, India
关键词
Big Data; Data Mining; Hadoop; Unstructured; KNOWLEDGE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:6
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