def generateCorpus(self, c_type = 'not'): corpus = Corpus(password='', db='project_major') if c_type == 'not': corpus.getTweetsWithNot() else: corpus.getTweets() self.corpus = corpus.dataSet self.negatives = corpus.negatives self.stopWords = corpus.stopWords corpus.close()
def scoring(self, method='zagibolov'): # Supply argument in Corpus to connect to databse. user, password and db. corpus = Corpus(password='', db='project_major') corpus.getTweets() dataset = corpus.dataSet preprocess = Preprocess('zagibolov', self.lexicons, self.negatives, self.stopWords) scoring = Scoring(method, self.lexicons, self.negatives, self.stopWords, self.seeds) j = 0 for data in dataset: preprocess.preprocessScoring(data) processed = preprocess.processed_data for data in processed: scoring.count(data['tweet']) ## print self.seeds preprocess.seeds = scoring.lexicon_count preprocess.processLexicon() scoring.lexicons = preprocess.lexicons ## print scoring.lexicon_count last_score = {} i = 0 for i in range(0,3): total = 0 j = 0 negative = 0 positive = 0 scoring.resetLexiconCount() ## print self.lexicons for data in processed: if j == 50: break j += 1 score = scoring.score(data) if score != 0: total += 1 if score < 0: negative += 1 else: positive += 1 scoring.adjustScoring() if last_score == {}: last_score = scoring.lexicons this_score = last_score else: this_score = scoring.lexicons if this_score == last_score: break else: last_score = this_score print this_score print "Total scored: " + str(total), "Negative: ", negative, "Positive: ", positive print this_score print "Total scored: " + str(total), "Negative: ", negative, "Positive: ", positive