def initialize_analysers(config):
"""Initialise analysers
"""
if 'skyttle' in ANALYZERS_TO_USE:
skyttle = Skyttle(mashape_auth=config['mashape_auth'],
language=config['language'])
ANALYZERS.append(skyttle)
if 'chatterbox' in ANALYZERS_TO_USE:
chatterbox = Chatterbox(mashape_auth=config['mashape_auth'],
language=config['language'])
ANALYZERS.append(chatterbox)
if 'datumbox' in ANALYZERS_TO_USE:
datumbox = Datumbox(api_key=config['datumbox_key'])
ANALYZERS.append(datumbox)
if 'repustate' in ANALYZERS_TO_USE:
repustate = Repustate(api_key=config['repustate_key'])
ANALYZERS.append(repustate)
if 'bitext' in ANALYZERS_TO_USE:
bitext = Bitext(user=config['bitext_user'],
password=config['bitext_pwd'],
language=config['language'])
ANALYZERS.append(bitext)
if 'semantria' in ANALYZERS_TO_USE:
semantria = Semantria(
consumer_key=config['semantria_consumer_key'],
consumer_secret=config['semantria_consumer_secret'])
ANALYZERS.append(semantria)
if 'viralheat' in ANALYZERS_TO_USE:
viralheat = Viralheat(api_key=config['viralheat_key'])
ANALYZERS.append(viralheat)
if 'lymbix' in ANALYZERS_TO_USE:
lymbix = Lymbix(api_key=config['lymbix_key'])
ANALYZERS.append(lymbix)
if 'aiapplied' in ANALYZERS_TO_USE:
aiapplied = AIApplied(api_key=config['aiapplied_key'],
language=config['language'])
ANALYZERS.append(aiapplied)
if 'sentigem' in ANALYZERS_TO_USE:
sentigem = Sentigem(api_key=config['sentigem_key'])
ANALYZERS.append(sentigem)
from classifiers.SentimentPolarityEmotion import SentimentPolarityEmotionClassifier
from pprint import pprint
from lymbix import Lymbix
apikey = "8a77503e17148fb5f3d5fd7d1e80ce86c23b6133"
# a few other api keys you use if this one has reached its limit
#apikey = "06bb0ef22cc21896451d7d9ed0f53eff6c99cd93"
#apikey = "1321dd7e3e05237514db9ae7812202c23f6b2f5e"
#SPEC = SentimentPolarityEmotionClassifier(apikey)
#result = SPEC.analyse("I love this movie")
#results = SPEC.analyseAll(["I love this movie", "I hate this movie"])
#pprint(results)
#print result["dominant_emotion"]
#print result["article_sentiment"]["sentiment"]
l = Lymbix(apikey)
r = l.tonalize_multiple(["I love you", "I hate you"])
print [i["article_sentiment"] for i in r]
f = open('../test set.txt', 'r')
from lymbix import Lymbix
lymbix = Lymbix('c6a2c5af610c650d2db35a98ab922741618b734e')
#rdata = lymbix.tonalize("My name is Paul.")
#print rdata['article_sentiment']
total = 0
count = 0
for line in f:
total += 1
tweet = line.split(' .:. ')
sentiment = tweet[0]
result = lymbix.tonalize(tweet[1])
# if sentiment == result['article_sentiment']['sentiment'].lower().replace('negative', 'neg').replace('positive', 'pos'):
# count += 1
# else:
# print total, result['article_sentiment']
score = result['article_sentiment']['score']
if abs(score) < 0.25:
sent_temp = 'neutral'
elif score > 0:
sent_temp = 'pos'
else:
from models.FinalDBUsers import FinalDBUsers
import re, string, pprint
from lymbix import Lymbix
def _processPunctuation(text):
t = re.sub("https?:\/\/.*(\s+|$)", '', text)
t = t.replace("\n", "").replace("'", "")
for p in string.punctuation:
t = t.replace(p, " "+p+" ")
return t
apikey = "8a77503e17148fb5f3d5fd7d1e80ce86c23b6133"
l = Lymbix(apikey)
fdbu = FinalDBUsers()
fdbt = FinalDBTweets()
users = fdbu._db.keys()
done = 0
total = len(users)
for i, uid in enumerate(users):
u = fdbu.get(uid)
texts = [_processPunctuation(t["text"]) for t in u["tweets"]]
if not fdbt.hasTweetsOfUser(uid) and len(texts) > 0:
r = l.tonalize_multiple(texts)
