Packages Needed

library(tuber)
        
library(magrittr)

library(tidyverse) 
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.4.0      ✔ purrr   1.0.1 
## ✔ tibble  3.1.8      ✔ dplyr   1.0.10
## ✔ tidyr   1.2.1      ✔ stringr 1.5.0 
## ✔ readr   2.1.3      ✔ forcats 0.5.2 
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ tidyr::extract()   masks magrittr::extract()
## ✖ dplyr::filter()    masks stats::filter()
## ✖ dplyr::lag()       masks stats::lag()
## ✖ purrr::set_names() masks magrittr::set_names()
library(purrr)

YouTube API key setup instructions

Login to Google’s developer console. On the dashboard click “Enable APIS and Services” and scroll through the list of APIs until you reach YouTube Data API v3.

To create credentials an OAuth client ID is required. Once this is created you will be provided with a client ID and client secret. Copy and paste both of these into R Studio to complete the following steps:

R Studio Setup

Save the two objects in RStudio

client_id <- "454647064650-djq2l0tjvhusctmdhmc7uqfa48b060cd.apps.googleusercontent.com"
client_secret <- "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"

Authenticate the application. Running this command will open a browser to sign into the Google account you used in the developer console.

yt_oauth(app_id = client_id,
         app_secret = client_secret,
         token = '')

After the sign in page, make sure you click “allow” when asked if you trust the application R Studio.

The following code shows a function of the YouTube API which allows you to download data of specific youtube playlists.

cody_ko_playlist_id <- stringr::str_split(
  string = "https://youtube.com/playlist?list=PL2ifFb9uR3cLlyW4OcCAeOJtiPjjHZb7_", 
  pattern = "=", 
  n = 2,
  simplify = TRUE)[ , 2]
cody_ko_playlist_id
## [1] "PL2ifFb9uR3cLlyW4OcCAeOJtiPjjHZb7_"
playlist_info <- tuber::get_playlist_items(filter = 
                          c(playlist_id = "PL2ifFb9uR3cLlyW4OcCAeOJtiPjjHZb7_"), 
                             part = "contentDetails",
                             max_results = 16)

After downloading the data, the YouTube API can also collect statistics such as views and likes, which can then be organised into a data frame.

video_ids <- playlist_info$items$contentDetails$resourceId$videoId
video_titles <- playlist_info$items$contentDetails$title
get_all_stats <- function(id) {
  tuber::get_stats(video_id = id)
} 

video_stats <- lapply(video_ids, function(x) get_video_stats(x, "statistics", yt))

video_data <- data.frame(video_title = video_titles,
                         views = sapply(video_stats, function(x) x$items$statistics$viewCount),
                         likes = sapply(video_stats, function(x) x$items$statistics$likeCount),
                         dislikes = sapply(video_stats, function(x) x$items$statistics$dislikeCount))