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| def individual_tweet_vectorizer(corpus, tweet, index=0, author=''): | |
| """ | |
| Formats a single tweet as a vector | |
| :param corpus: list of all words in tweets | |
| :param tweet: tweet to be vectorized | |
| :param index: index of tweet in main list of tweets | |
| :param author: Trump or general | |
| :return: Single tweet in vector form | |
| """ | |
| individual_tweet_vector = np.zeros((1, len(corpus) + 2), dtype=int) | |
| for word in range(len(corpus)): | |
| if corpus[word] in tweet: | |
| individual_tweet_vector[0][word] = 1 | |
| if author != '': # If author is specified, set the last value of the tweet vector to 1 | |
| individual_tweet_vector[0][-1] = 1 | |
| individual_tweet_vector[0][-2] = index # Keep track of index of tweet for interpretation | |
| return individual_tweet_vector |
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