Playing around with the updated `scholar` package.
This is a post to breadcrumb the migration of the previous website. Turns out that updating the hugo package, the blogdown package, the academic theme, and installing the Rstudio preview build all in the same day was a good way to blow up the previous iteration.
One of the wonderful features of the R statistical universe is the number of free, high-quality instructional materials available. Throughout the remainder of the course, we will be learning and working from the R for Data Science book (you’ll see this book shorthanded as R4DS in this course and all over the web), by two giants of the R space: Hadley Wickham and Garrett Grolemund .
Presented at the Political Research Colloquium, University of Utah, Oct. 30, 2020
Libraries library(tidytext) library(ggthemes) library(tidyverse) library(ggplot2) library(dplyr) library(scales) Load Previous STM Objects I have previously run stm models for topics ranging from 3 to 25. Based on the fit indices, a six-topic model was selected.
This report was generated on 2020-12-30, as a demo of textclean from https://github.com/trinker/textclean#check-text
This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.
I really appreciate Dan Quintana for his walkthrough on getting an Academic themed website up and running.
Thank you to Peter Paul Pichler for his script adapated from Lorenzo Busetto’s original script to import publication data from bibtex files (I use Zotero, but other citation software should work fine).