twitter analysis in R clean tweets
df <- tm_map(df, tolower)
twitter analysis in R clean tweets
df <- tm_map(df, tolower)
twitter analysis in R clean tweets
clean_tweet4 <- str_replace_all(clean_tweet3, "https://t.co/[a-z,A-Z,0-9]*","") clean_tweet5 <- str_replace_all(clean_tweet4, "http://t.co/[a-z,A-Z,0-9]*","")
twitter analysis in R clean tweets
clean_tweet = gsub("&", "", unclean_tweet) clean_tweet = gsub("(RT|via)((?:\\b\\W*@\\w+)+)", "", clean_tweet) clean_tweet = gsub("@\\w+", "", clean_tweet) clean_tweet = gsub("[[:punct:]]", "", clean_tweet) clean_tweet = gsub("[[:digit:]]", "", clean_tweet) clean_tweet = gsub("http\\w+", "", clean_tweet) clean_tweet = gsub("[ \t]{2,}", "", clean_tweet) clean_tweet = gsub("^\\s+|\\s+$", "", clean_tweet)
twitter analysis in R clean tweets
Error in stri_replace_all_regex(string, pattern, fix_replacement(replacement), : Syntax error in regexp pattern. (U_REGEX_RULE_SYNTAX)
twitter analysis in R clean tweets
#get rid of unnecessary spaces clean_tweet <- str_replace_all(clean_tweet," "," ") # Get rid of URLs clean_tweet <- str_replace_all(clean_tweet, "http://t.co/[a-z,A-Z,0-9]*{8}","") # Take out retweet header, there is only one clean_tweet <- str_replace(clean_tweet,"RT @[a-z,A-Z]*: ","") # Get rid of hashtags clean_tweet <- str_replace_all(clean_tweet,"#[a-z,A-Z]*","") # Get rid of references to other screennames clean_tweet <- str_replace_all(clean_tweet,"@[a-z,A-Z]*","")
twitter analysis in R clean tweets
df <- tm_map(df, removePunctuation)
twitter analysis in R clean tweets
# Get rid of URLs clean_tweet <- str_replace_all(clean_tweet, "http://t.co/[a-z,A-Z,0-9]*{8}","")
twitter analysis in R clean tweets
library(tidyverse) clean_tweets <- function(x) { x %>% str_remove_all(" ?(f|ht)(tp)(s?)(://)(.*)[.|/](.*)") %>% str_replace_all("&", "and") %>% str_remove_all("[[:punct:]]") %>% str_remove_all("^RT:? ") %>% str_remove_all("@[[:alnum:]]+") %>% str_remove_all("#[[:alnum:]]+") %>% str_replace_all("\\\n", " ") %>% str_to_lower() %>% str_trim("both") } tweets %>% clean_tweets
twitter analysis in R clean tweets
df <- tm_map(df, removeNumbers)
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