An Analysis of Different Factors' Contribution to Facebook Page Likes
Guodong Ma · CREATIVE ECONOMY · 2022
On the basis of big data regarding a publicly-available dataset about statistics of 500 posts published in 2014 on Facebook's page of a worldwide renowned cosmetic brand, this research aims to exhibit a comprehensive and rational deducing progress in character with the justified and formulated variables and visible results to be instrumental in the analysis of the factors' contribution to page total likes. In this paper, the generalized linear regression on the page total likes against the candidate covariates is drew to analysis, Bayesian lasso was used for selecting the essential variables and the Metropolis-Hastings algorithm was applied to obtain the posterior draws of the parameters.