This is an R package that allow researchers of the Center for Communication and Civic Engagement (CCCE) at the University of Washington to analyze and study social media data.
To install this ccceR package use the install_github()
function of the devtools
package.
install.packages("devtools")
library(devtools)
install_github("CasAndreu/ccceR")
library(ccceR)
xls
files from Crimson Hegaxon
If you are using an Excel file downloaded from Crimson Hexagon, you need to do some simple pre-processing tasks in order to have a dataset you can apply the ccceR
functions (a dataset with meaningful variable names).
To read the xls
file into R, you can use the package rio
. If you don't have the package, install it first. Then load it.
install.packages("rio")
library(rio)
Read and pre-process the data in R
file_path <- "path/to/the/xls/file"
raw_dataset <- import(file_path)
colnames(raw_dataset) <- raw_dataset[1, ] # The name of the variables are in the first row
dataset <- raw_dataset[2:nrow(raw_dataset), ] # Getting rid of the first row of the dataset
add_rt_dummy()
This function adds a RT dummy variable into the dataset to indicate which messages are RTs. If the message is a retweet, RT
== 1.
new_dataset <- add_rt_dummy(dataset, "Contents")
add_link_dummy()
This function adds a dummy variable to the dataset indicating which messages contain at least one URL. If the message contains URLs, link_dummy
== 1.
new_dataset <- add_link_dummy(dataset, "Contents")
add_tweet_id()
This function adds a variable to the datset with the tweet id (tweet_id
).
new_dataset <- add_tweet_id(dataset, "URL")
add_links_url()
This function adds 2 variables to the dataset with "shortened" (links_short_url
) and "full" (links_full_url
) URLs in the text messages.
new_dataset <- add_links_url(dataset, "Contents")
add_image_dummy()
This function adds a dummy variable to the dataset (image_dummy
) indicating which messages contain links to images.
new_dataset <- add_image_dummy(dataset, "links_full_url")
download_images()
This function downloads images in tweets to a directory given by the user, and it also adds a variable to the dataset indicating the id of the tweet images.
new_dataset_with_image_id <- download_images(dataset, "links_full_url", "path/to/a/directory")
as_data_frame()
This funciton transforms all variables of a dataset into character variables so datasets with list variables can be written out inot a CSV file.
new_dataset <- as_data_frame(dataset)
write.csv(new_dataset, "new_dataset.csv", row.names = FALSE)
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