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# Get twitter data
trainer <- search_tweets(q = "Guardiola", n=18000, type='mixed', lang="en") 
# Assign relevant columns
keep_cols <- c("user_id", "screen_name", "created_at", "text", "source", "is_quote","is_retweet", "favorite_count", "retweet_count","quote_count","reply_count","hashtags","retweet_text", "followers_count", "verified")
# Filter to relevant columns
trainer <- trainer %>% 
  select(keep_cols)
# Source for URL removal: https://www.earthdatascience.org/courses/earth-analytics/get-data-using-apis/text-mining-twitter-data-intro-r/
trainer$stripped_text <- gsub("http.*","",  trainer$text) # Remove http
trainer$stripped_text <- gsub("https.*","", trainer$stripped_text) # Remove https

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library(fmsb)

df <- read_csv("imdb_top_250_sentiments.csv", col_types = c(col_character(), 
                                                 col_character(),
                                                 col_double(),
                                                 col_double(),
                                                 col_character(),
                                                 col_character()))

counts <- as.data.frame(table(df$Overall_sentiment))

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