def get_local_features(self, text):
feature_vector = dict()
text_obj = TextObj(text)
feature_extractor.get_ngrams(feature_vector, text_obj.tokens)
feature_extractor.get_ngrams(feature_vector, text_obj.tokens, n=2)
feature_extractor.get_initialisms(feature_vector, text_obj.tokens)
feature_extractor.get_basic_lengths(feature_vector, text_obj.text, text_obj.sentences, text_obj.tokens)
feature_extractor.get_repeated_punct(feature_vector, text_obj.text)
feature_extractor.get_LIWC(feature_vector, text_obj.text)
return feature_vector
def build_features(body, subject, stemmer=None, wn=None, features=[]):#'bow_disc']): #'bow_disc', 'liwc'
all_bow = dict()
body_bow = dict()
subj_bow = dict()
stemmed_body = stemmer.stem(body)
stemmed_subj = stemmer.stem(subject)
tokens_body = wordpunct_tokenize(stemmed_body)
tokens_subj = wordpunct_tokenize(stemmed_subj)
all_bow = {'bow_{}'.format(token): True for token in tokens_body + tokens_subj}
if 'bow_desc' in features:
body_bow = {'body_{}'.format(token): True for token in tokens_body}
subj_bow = {'subject_{}'.format(token): True for token in tokens_subj}
polarity = defaultdict(int)
subj_liwc = dict()
body_liwc = dict()
if 'liwc' in features:
get_LIWC(subj_liwc, stemmed_subj)
get_LIWC(body_liwc, stemmed_body)
if 'polarity' in features:
for token in tokens_subj + tokens_body:
result = msol.lookup(token)
if result == 'negative' or result == 'positive':
polarity[result] += 1
all_wn = dict()
if 'wn' in features:
for token in tokens_body + tokens_subj:
result = wn.lookup(token)
if len(result) > 0:
for element in result:
all_wn['WN_{}'.format(element)] = True
return combine_dicts(all_bow,
subj_bow,
body_bow,
all_wn,
prepend_key(subj_liwc, 'SUBJLIWC'),
prepend_key(body_liwc, 'BODYLIWC'),
polarity,
)