Quality Assessment Approaches in Popularity Prediction of Social Media Using Big Data Analytics

Popularity Analysis in social media has taken a great leap in analysing its importance among general public as many high ranked professionals around the country has turned to social media for their marketing, updated information and opinion sharing etc., The objective of this paper is to analyse the quality assessment methods in existence for the popularity of a post or news that are determined by various attributes like shares, likes, comments and recommend to a friend. Hence a data analysis is carried out with Facebook public audience opinions and views for the posts created by high ranked professionals in various fields like politics, sports, academics etc., The Proposed model includes an improved hybrid PageRank big data model sufficient for increasing data management and its scalability. The proposed model was implemented using R-Studio and Tableau in big data and the results are presented with various quality factor analysis on the popularity of the person in social media.