Predictive analytics using Social Big Data and machine learning

TL;DR

This paper discusses the importance of predictive analytics in social big data, introduces a framework, reviews algorithms and tools, and provides a case study demonstrating their practical utility.

Contribution

It presents a comprehensive framework for social big data predictive analytics and reviews algorithms, tools, and applications with empirical validation.

Findings

Predictive analytics enhances insights from social big data.

Various algorithms are effective in different social data applications.

Case study confirms the utility of predictive analytics in social data analysis.

Abstract

The ever-increase in the quality and quantity of data generated from day-to-day businesses operations in conjunction with the continuously imported related social data have made the traditional statistical approaches inadequate to tackle such data floods. This has dictated researchers to design and develop advance and sophisticated analytics that can be incorporated to gain valuable insights that benefit the business domain. This chapter sheds the light on core aspects that lay the foundations for social big data analytics. In particular, the significance of predictive analytics in the context of SBD is discussed fortified with presenting a framework for SBD predictive analytics. Then, various predictive analytical algorithms are introduced with their usage in several important application and top-tier tools and APIs. A case study on using predictive analytics to social data is provided supported with experiments to substantiate the significance and utility of predictive analytics.