storywranglr

This package makes it easy to explore trends in Twitter data using the Storywrangler application programming interface (API). Data is returned in a tidy tibble to make it easy to work with and visualize.

For more details about Storywrangler, please see:

• API documentation: https://github.com/janeadams/storywrangler
• Academic paper describing uses: https://advances.sciencemag.org/content/7/29/eabe6534.full

Installation

You can install the developer version, which has the latest bugfixes and features, with:

devtools::install_github("chris31415926535/storywranglr")

You can install the released version of storywranglr from CRAN with:

install.packages("storywranglr")

Examples

Let’s use storywranglr::ngrams() to chart the popularity of the 2-gram “black friday” over time. Not surprisingly, it looks like there’s an annual peak around Black Friday.

library(storywranglr)
library(tidyverse)

result <- storywranglr::ngrams("black friday")

result %>%
  ggplot(aes(x=date, y=rank)) +
  geom_point() +
  theme_minimal() +
  scale_y_continuous(trans = "reverse") +
  labs(title = "Twitter rank popularity of 2-gram 'black friday'",
       subtitle = "Data from Storywrangler ngrams API",
       x = "Date",
       y = "Rank")

Now using storywrangler::zipf(), let’s find the 10 top 2-grams from January 6, 2021. “the Capitol” made the top 10, and if we got a longer list we could expect to see other thematically related terms.

result <- zipf("2021-01-06", max = 10, ngrams = 2)

knitr::kable(result)