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clean_tweets()
Create a clean corpus of all the used words in a users tweets.
count_tweets()
Count the propotion of different sentiment tweets in a labelled sentiment dataframe
count_words()
Create a dataframe with all the words in a users tweets and how often they appear.
create_wordcloud()
Create a wordcloud of a users tweets.
generalPreprocessing()
Perform general preprocessing on df. Removes retweets/favourites and cleans URLs, Mentions, and Numbers.
load_twitter_by_keywords()
Load dataframe which contains specific keyword return as a dataframe with total tweets
load_twitter_by_user()
Load dataframe which contains specific user and return as a dataframe with total tweets
sentiment_labeler()
Labelling each row in a given column of tweets/text with positive, negative or neutral sentiment
user_info()
Title Take four input parameters and stored in a list object
named "user_info" with keys "consumer_key", "consumer_secret", "access_token", and "access_token_secret".