# Extract their word counts
corpus, corpus_path = get_subreddit_vocabularies()
print 'TF-IDF corpus saved to %s' % corpus_path
# Get the top words by subreddit
top_terms_path = save_subreddit_top_terms(corpus)
print 'Top terms saved to %s' % corpus_path
# Get the swearword frequency
swearword_frequency = get_swearword_counts(corpus)
print 'Normalized swearword frequency:'
for subreddit, frequency in swearword_frequency.items():
print '%s, %s' % (subreddit, frequency)
# Get the average word length
print '\nAverage word length by subreddit:'
word_lengths = get_vocabulary_sophistication(corpus)
for subreddit, frequency in word_lengths.items():
print '%s, %s' % (subreddit, frequency)
#######################
# MACHINE LEARNING DEMO
#######################
# Collect the comments for a particular user and determine which subreddit their comments best match up with
counter = RedditWordCounter(USERNAME)
corpus = TfidfCorpus(os.path.join(SAVE_DIR, CORPUS_FILE))
user_comments = counter.user_comments('way_fairer')
corpus.train_classifier(classifier_type='LinearSVC', tfidf=True)
print corpus.classify_document(user_comments)
# Extract their word counts
corpus, corpus_path = get_subreddit_vocabularies()
print 'TF-IDF corpus saved to %s' % corpus_path
# Get the top words by subreddit
top_terms_path = save_subreddit_top_terms(corpus)
print 'Top terms saved to %s' % corpus_path
# Get the swearword frequency
swearword_frequency = get_swearword_counts(corpus)
print 'Normalized swearword frequency:'
for subreddit, frequency in swearword_frequency.items():
print '%s, %s' % (subreddit, frequency)
# Get the average word length
print '\nAverage word length by subreddit:'
word_lengths = get_vocabulary_sophistication(corpus)
for subreddit, frequency in word_lengths.items():
print '%s, %s' % (subreddit, frequency)
#######################
# MACHINE LEARNING DEMO
#######################
# Collect the comments for a particular user and determine which subreddit their comments best match up with
counter = RedditWordCounter(USERNAME)
corpus = TfidfCorpus(os.path.join(SAVE_DIR, CORPUS_FILE))
user_comments = counter.user_comments('way_fairer')
corpus.train_classifier(classifier_type='LinearSVC', tfidf=True)
print corpus.classify_document(user_comments)
