tweet.py 文件源码

def person_connotation(tweet, name):
    """
    Decide whether a person is talked favorably about or not, based on the
    tone of the sentences in which their name appears
    """
    twtcontent = sent_tokenize(tweet)
    overall = {'compound': 0, 'neg': 0, 'neu': 0, 'pos': 0}
    mentions = 0
    # analyze each sentence talking about `name` person
    for s in twtcontent:
        tags = get_tweet_tags(s)
        # if the name appears in the tagged sentence, get its tone
        if (name, 'NNP') in tags:
            sentence = util.untag(tags)
            scores = tweet_connotation(' '.join(sentence))
            # add it up to the overall tweet's tone
            for i, z in enumerate(scores):
                overall[z] += scores[z]
            mentions += 1
    # averaging all sentences' scores. don't wanna divide by zero now do we
    if mentions != 0:
        for v in overall:
            overall[v] = round(overall[v] / mentions, 3)
    return overall