Predictive Analytics Accomplished by the Utilization of Social Big Data and Machine Learning

The ever-increasing quality and quantity of data generated from day-to-day business operations, in conjunction with the continuously imported related social data, has rendered the traditional statistical approaches inadequate to deal with such data floods. This inadequacy can be attributed to the fact that traditional statistical methods were developed before the advent of the internet. Because of this, academics have been compelled to design and develop advanced and complex analytics that may be incorporated to acquire useful insights that are beneficial to the commercial area. This chapter shines a light on fundamental characteristics that are the building blocks for social big data analytics and lays out those building blocks. In particular, the importance of predictive analytics within the scope of SBD is examined, and this analysis is bolstered by the presentation of a framework for SBD predictive analytics. After that, a number of different predictive analytical algorithms are discussed, along with their implementation in a number of essential applications, top-tier tools, and APIs. Experiments are presented alongside a case study that demonstrates how predictive analytics may be used to social data. This is done to demonstrate the significance and practicality of predictive analytics.