Optimising Web Shares Using Model Optimization for Different Article Types

ST 558 Project 2

Online News Popularity Data Set summarizes a heterogeneous set of features about articles published by Mashable in a period of two years. The goal is to predict the number of shares in social networks (popularity). Here we first showed some summary statistics and plots about the data grouped by weekdays. Then we create several models to predict the response, shares in different channels. The performance of these models will be evaluated by RMSE. The model having the lowest RMSE will be selected as a winner.

Used R packages: rmarkdown usethis tidyverse caret rsample corrplot mctest leaps tree randomForest

The analysis for Lifestyle Articles
The analysis for Entertainment Articles
The analysis for Business Articles
The analysis for Technology Articles
The analysis for World Articles
The analysis for Social/Medical Articles