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
