Update for new repo home

Author: juliasilge

04-word-combinations.Rmd

@@ -2,7 +2,7 @@
 
 So far we've considered words as individual units, and considered their relationships to sentiments or to documents. However, many interesting text analyses are based on the relationships between words, whether examining which words tend to follow others immediately, or that tend to co-occur within the same documents.
 
-In this chapter, we'll explore some of the methods tidytext offers for calculating and visualizing relationships between words in your text dataset. This includes the `token = "ngrams"` argument, which tokenizes by pairs of adjacent words rather than by individual ones. We'll also introduce two new packages: [ggraph](https://github.com/thomasp85/ggraph), which extends ggplot2 to construct network plots, and [widyr](https://github.com/dgrtwo/widyr), which calculates pairwise correlations and distances within a tidy data frame. Together these expand our toolbox for exploring text within the tidy data framework.
+In this chapter, we'll explore some of the methods tidytext offers for calculating and visualizing relationships between words in your text dataset. This includes the `token = "ngrams"` argument, which tokenizes by pairs of adjacent words rather than by individual ones. We'll also introduce two new packages: [ggraph](https://github.com/thomasp85/ggraph), which extends ggplot2 to construct network plots, and [widyr](https://github.com/juliasilge/widyr), which calculates pairwise correlations and distances within a tidy data frame. Together these expand our toolbox for exploring text within the tidy data framework.
 
 ## Tokenizing by n-gram
 
@@ -354,7 +354,7 @@ Tidy data is a useful structure for comparing between variables or grouping by r
 knitr::include_graphics("images/tmwr_0407.png")
 ```
 
-We'll examine some of the ways tidy text can be turned into a wide matrix in Chapter \@ref(dtm), but in this case it isn't necessary. The [widyr](https://github.com/dgrtwo/widyr) package makes operations such as computing counts and correlations easy, by simplifying the pattern of "widen data, perform an operation, then re-tidy data" (Figure \@ref(fig:widyr)). We'll focus on a set of functions that make pairwise comparisons between groups of observations (for example, between documents, or sections of text).
+We'll examine some of the ways tidy text can be turned into a wide matrix in Chapter \@ref(dtm), but in this case it isn't necessary. The [widyr](https://github.com/juliasilge/widyr) package makes operations such as computing counts and correlations easy, by simplifying the pattern of "widen data, perform an operation, then re-tidy data" (Figure \@ref(fig:widyr)). We'll focus on a set of functions that make pairwise comparisons between groups of observations (for example, between documents, or sections of text).
 
 ### Counting and correlating among sections
 

07-tweet-archives.Rmd

@@ -309,7 +309,7 @@ word_by_rts %>%
   arrange(desc(retweets))
 ```
 
-At the top of this sorted data frame, we see tweets from Julia and David about packages that they work on, like [gganimate](https://github.com/dgrtwo/gganimate) and [tidytext](https://cran.r-project.org/package=tidytext). Let's plot the words that have the highest median retweets for each of our accounts (Figure \@ref(fig:plotrts)).
+At the top of this sorted data frame, we see tweets from Julia and David about packages that they work on, like [gganimate](https://gganimate.com/) and [tidytext](https://cran.r-project.org/package=tidytext). Let's plot the words that have the highest median retweets for each of our accounts (Figure \@ref(fig:plotrts)).
 
 ```{r plotrts, dependson = "word_by_rts", fig.width=8, fig.height=4, fig.cap="Words with highest median retweets"}
 word_by_rts %>%

README.md

@@ -1,6 +1,6 @@
 This is the repo for the book [**Text Mining with R: A Tidy Approach**](http://tidytextmining.com/), by Julia Silge and David Robinson.
 
-[![Build Status](https://github.com/dgrtwo/tidy-text-mining/workflows/bookdown/badge.svg)](https://github.com/dgrtwo/tidy-text-mining/actions)
+[![Build Status](https://github.com/juliasilge/tidy-text-mining/workflows/bookdown/badge.svg)](https://github.com/juliasilge/tidy-text-mining/actions)
 [![Netlify Status](https://api.netlify.com/api/v1/badges/2e9741eb-97a9-4d49-949e-1d668735d836/deploy-status)](https://app.netlify.com/sites/tidy-text-mining/deploys)
 
-Please note that this work is written under a [Contributor Code of Conduct](CONDUCT.md) and released under a [CC-BY-NC-SA license](https://creativecommons.org/licenses/by-nc-sa/3.0/us/). By participating in this project (for example, by submitting a [pull request](https://github.com/dgrtwo/tidy-text-mining/issues) with suggestions or edits) you agree to abide by its terms.
+Please note that this work is written under a [Contributor Code of Conduct](CONDUCT.md) and released under a [CC-BY-NC-SA license](https://creativecommons.org/licenses/by-nc-sa/3.0/us/). By participating in this project (for example, by submitting a [pull request](https://github.com/juliasilge/tidy-text-mining/issues) with suggestions or edits) you agree to abide by its terms.

_output.yml

@@ -3,7 +3,7 @@ bookdown::bs4_book:
     primary: "#5b7886"
     base_font:
       google: Roboto
-  repo: https://github.com/dgrtwo/tidy-text-mining
+  repo: https://github.com/juliasilge/tidy-text-mining
   includes:
     in_header: _includes/analytics.html
 
@@ -17,7 +17,7 @@ bookdown::gitbook:
       after: |
         <li><a href="https://github.com/rstudio/bookdown" target="blank">Published with bookdown</a></li>
     edit:
-      link: https://github.com/dgrtwo/tidy-text-mining/edit/master/%s
+      link: https://github.com/juliasilge/tidy-text-mining/edit/master/%s
   includes:
     in_header: _includes/analytics.html
 

index.Rmd

@@ -12,7 +12,7 @@ biblio-style: apalike
 link-citations: true
 links-as-notes: true
 colorlinks: true
-github-repo: dgrtwo/tidy-text-mining
+github-repo: juliasilge/tidy-text-mining
 cover-image: images/cover.png
 url: https://www.tidytextmining.com/
 description: "A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools"
@@ -29,7 +29,7 @@ knitr::write_bib(c(
 
 <a href="http://amzn.to/2tZkmxG"><img src="images/cover.png" width="350" height="460" alt="Buy from Amazon" class="cover" /></a>
 
-This is the [website](http://tidytextmining.com/) for *Text Mining with R*! Visit the [GitHub repository for this site](https://github.com/dgrtwo/tidy-text-mining), find the book at [O'Reilly](http://www.jdoqocy.com/click-4428796-11290546?url=http%3A%2F%2Fshop.oreilly.com%2Fproduct%2F0636920067153.do%3Fcmp%3Daf-strata-books-video-product_cj_0636920067153_%25zp&cjsku=0636920067153), or [buy it on Amazon](http://amzn.to/2tZkmxG).
+This is the [website](http://tidytextmining.com/) for *Text Mining with R*! Visit the [GitHub repository for this site](https://github.com/juliasilge/tidy-text-mining), find the book at [O'Reilly](http://www.jdoqocy.com/click-4428796-11290546?url=http%3A%2F%2Fshop.oreilly.com%2Fproduct%2F0636920067153.do%3Fcmp%3Daf-strata-books-video-product_cj_0636920067153_%25zp&cjsku=0636920067153), or [buy it on Amazon](http://amzn.to/2tZkmxG).
 
 This work by [Julia Silge](http://juliasilge.com/) and [David Robinson](http://varianceexplained.org/) is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/3.0/us/">Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License</a>.
 
@@ -96,7 +96,7 @@ We do assume that the reader is at least slightly familiar with dplyr, ggplot2,
 
 ## Using code examples {-}
 
-This book was written in [RStudio](http://www.rstudio.com/ide/) using [bookdown](http://bookdown.org/). The [website](https://www.tidytextmining.com/) is hosted via [Netlify](http://netlify.com/), and automatically built after every push by [GitHub Actions](https://help.github.com/actions). While we show the code behind the vast majority of the analyses, in the interest of space we sometimes choose not to show the code generating a particular visualization if we've already provided the code for several similar graphs. We trust the reader can learn from and build on our examples, and the code used to generate the book can be found in our [public GitHub repository](https://github.com/dgrtwo/tidy-text-mining). We generated all plots in this book using [ggplot2](https://ggplot2.tidyverse.org/) and its light theme (`theme_light()`).
+This book was written in [RStudio](http://www.rstudio.com/ide/) using [bookdown](http://bookdown.org/). The [website](https://www.tidytextmining.com/) is hosted via [Netlify](http://netlify.com/), and automatically built after every push by [GitHub Actions](https://help.github.com/actions). While we show the code behind the vast majority of the analyses, in the interest of space we sometimes choose not to show the code generating a particular visualization if we've already provided the code for several similar graphs. We trust the reader can learn from and build on our examples, and the code used to generate the book can be found in our [public GitHub repository](https://github.com/juliasilge/tidy-text-mining). We generated all plots in this book using [ggplot2](https://ggplot2.tidyverse.org/) and its light theme (`theme_light()`).
 
 This version of the book was built with `r R.version.string` and the following packages:
 
@@ -123,7 +123,7 @@ We received thoughtful, thorough technical reviews that improved the quality of
 ```{r, eval = FALSE, echo = FALSE}
 library(tidyverse)
 contribs_all_json <- gh::gh("/repos/:owner/:repo/contributors",
-  owner = "dgrtwo",
+  owner = "juliasilge",
   repo = "tidy-text-mining",
   .limit = Inf
 )