def process_comment(data,**kwargs):
logging.info("$$$$ nlp.process_comment[]")
cache = voxpop.VPE.get_caches().get(key=data['cache_id'])
try:
comment = cache.get_cached()[data['comment_id']]
except KeyError:
logging.info("$$$$ nlp.process_comment: ITEM NOT FOUND IN MEMORY ["+data['comment_id']+"]")
return False
tokens = nltk.word_tokenize(nltk.clean_html(comment['commentBody']))
words = {'positive':[], 'negative':[], 'strong':[], 'weak':[], 'active':[], 'passive':[]}
for token in tokens:
with lasswell_lock:
parsed = lp.parse(token)
if parsed:
logging.info(token + str(parsed))
if parsed[0] == 1:
words['positive'].append(token)
elif parsed[0] == -1:
words['negative'].append(token)
if parsed[1] == 1:
words['strong'].append(token)
elif parsed[1] == -1:
words['weak'].append(token)
if parsed[2] == 1:
words['active'].append(token)
elif parsed[2] == -1:
words['passive'].append(token)
comment['words'] = words
cache.set(data['comment_id'], comment)
return True
def parse(self, text): adjectives = [] for w,pos in nltk.pos_tag(nltk.word_tokenize(nltk.clean_html(text))): if pos == "JJ": adjectives.append([w,evaluative(w),potency(w),activity(w)]) return adjectives