tidytext extract url r

1. Load the necessary packages:

library(tidyverse) - This loads the tidyverse package, which is a collection of R packages designed for data manipulation and visualization.

library(tidytext) - This loads the tidytext package, which provides functions for text mining and analysis.

1. Read the data:

data <- read_csv("data.csv") - This reads the data from a CSV file called "data.csv" and stores it in the variable "data".

1. Tokenize the text:

data_tokenized <- data %>% unnest_tokens(word, text) - This tokenizes the text column in the data by separating it into individual words. The result is stored in a new variable called "data_tokenized".

1. Remove stop words:

data_filtered <- data_tokenized %>% anti_join(stop_words) - This removes common stop words (e.g., "the", "and", "is") from the tokenized data. The result is stored in a new variable called "data_filtered".

1. Count word frequencies:

word_counts <- data_filtered %>% count(word, sort = TRUE) - This counts the frequency of each word in the filtered data and sorts the result in descending order. The result is stored in a new variable called "word_counts".

1. Extract URLs:

url <- word_counts %>% filter(str_detect(word, "^http")) - This filters the word_counts data to extract only the words that start with "http", indicating URLs. The result is stored in a new variable called "url".

1. View the extracted URLs:

url - This displays the extracted URLs on the console.

Note: Please ensure that you have the "tidyverse" and "tidytext" packages installed before running this code.