def create_word_bigram_scores():
    posdata = tp.seg_fil_txt("/home/hadoop/goodnew.txt")
    negdata = tp.seg_fil_txt("/home/hadoop/badnew.txt")
    
    posWords = list(itertools.chain(*posdata))
    negWords = list(itertools.chain(*negdata))

    bigram_finderr = BigramCollocationFinder.from_words(posWords)
    bigram_finder = BigramCollocationFinder.from_words(negWords)
    posBigrams = bigram_finderr.nbest(BigramAssocMeasures.chi_sq,350000)
    negBigrams = bigram_finder.nbest(BigramAssocMeasures.chi_sq,350000)

    pos = posWords + posBigrams
    neg = negWords + negBigrams

    word_fd = FreqDist()
    cond_word_fd = ConditionalFreqDist()
    for word in pos:
        word_fd.inc(word)
        cond_word_fd['pos'].inc(word)
    for word in neg:
        word_fd.inc(word)
        cond_word_fd['neg'].inc(word)

    pos_word_count = cond_word_fd['pos'].N()
    neg_word_count = cond_word_fd['neg'].N()
    total_word_count = pos_word_count + neg_word_count

    word_scores = {}
    for word, freq in word_fd.iteritems():
        pos_score = BigramAssocMeasures.chi_sq(cond_word_fd['pos'][word], (freq, pos_word_count), total_word_count)
        neg_score = BigramAssocMeasures.chi_sq(cond_word_fd['neg'][word], (freq, neg_word_count), total_word_count)
        word_scores[word] = pos_score + neg_score

    return word_scores
def create_word_scores():
    posdata = tp.seg_fil_txt("/home/hadoop/goodnew.txt")
    negdata = tp.seg_fil_txt("/home/hadoop/badnew.txt")
    posWords = list(itertools.chain(*posdata))
    negWords = list(itertools.chain(*negdata))
    word_fd = FreqDist()
    cond_word_fd = ConditionalFreqDist()
    for word in posWords:
        word_fd.inc(word)
        cond_word_fd['pos'].inc(word)
    for word in negWords:
        word_fd.inc(word)
        cond_word_fd['neg'].inc(word)
    pos_word_count = cond_word_fd['pos'].N()
    neg_word_count = cond_word_fd['neg'].N()
    total_word_count = pos_word_count + neg_word_count
    word_scores = {}
    for word, freq in word_fd.iteritems():
        pos_score = BigramAssocMeasures.chi_sq(cond_word_fd['pos'][word], (freq, pos_word_count), total_word_count)
        neg_score = BigramAssocMeasures.chi_sq(cond_word_fd['neg'][word], (freq, neg_word_count), total_word_count)
        word_scores[word] = pos_score + neg_score
    return word_scores