Predictive Analytics of Popularity of News in social media with Key Performance Indicators using Bigdata Analytics

It is evident from recent impact from people around the world that everyone was interested in reading news using online applications and tools. The news published in social media platforms contain various information that might provide source to identify the popularity of the person. Key Performance Indicators (KPI) are special features that are capable of measuring the quality of the predictive data using quantifiable components. The major objective of this research paper is to perform predictive analytics of the various parameters used to assess popularity of news being shared in social media using KPI in Bigdata Analytics. The dataset for popularity of news was selected with 61 features and 39644 records to determine the Key Performance Indicators in performing the prediction and analysis of popularity of a person with significant success. The prediction was performed in WEKA using classification and cluster analysis whereas the analytics was performed using Tableau to find out the KPI of the dataset. The research identified six KPI at the end of the outcomes that would be regarded as key to perform any analysis.