knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
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:
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")
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)
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