def addReview(self, reviewDict):
polarity = reviewDict["sentiment"]
tempDict = {}
tempDict["date"] = dt.datetime.strptime(reviewDict["date"], '%Y-%m-%d').date().year
tempDict["negative"] = 0
tempDict["positive"] = 0
tempDict["neutral"] = 0
tempDict["sentiment"] = polarity
tempDict["count"] = 1
tempDict["stars"] = reviewDict["stars"]
if polarity < -0.05:
tempDict["negative"] += 1
for word in tm.getWordVector(reviewDict["text"]):
self.negativeCorpus.append(word)
elif polarity > 0.05:
tempDict["positive"] += 1
else:
tempDict["neutral"] += 1
isPresent = False
for item in self.dict["violations"]:
if item["date"] == tempDict["date"]:
if "sentiment" not in item:
item["negative"] = tempDict["negative"]
item["positive"] = tempDict["positive"]
item["neutral"] = tempDict["neutral"]
item["sentiment"] = tempDict["sentiment"]
item["stars"] = tempDict["stars"]
item["count"] = tempDict["count"]
else:
item["negative"] += tempDict["negative"]
item["positive"] += tempDict["positive"]
item["neutral"] += tempDict["neutral"]
item["sentiment"] += tempDict["sentiment"]
item["stars"] += tempDict["stars"]
item["count"] += tempDict["count"]
isPresent = True
if not isPresent:
self.dict["violations"].append(tempDict)
# "Fast Food Items",
# "Seafood Menu Items",
# "Ambiance & Hospitality",
# "Dinner & Drinks"]
# pickle.dump(topics, open("trained-model-topics",'w'))
# topics = []
topics = pickle.load(file("trained-model-topics"))
ldaModel = pickle.load(file("trained-negative-model"))
ldaDictionary = pickle.load(file("model-dictionary"))
print "Dictionary and Trained Model loaded!"
# print ldaModel.show_topics(num_topics=10, num_words=10, formatted=False)
for item in reviewsSet:
topics_found = []
models = ldaModel[ldaDictionary.doc2bow(tm.getWordVector(item))]
models = sorted(models, key=lambda k: k[1], reverse = True)
# print models
# if len(models) == 2:
# print "-"*5 + str(topics[models[0][0]]) + "-"*5 + str(topics[models[1][0]]) + "-"*5
# print item
for single_topic in models:
topics_found.append(topics[single_topic[0]])
if len(topics_found) > 2:
break
print "-"*5 + str(topics_found) + "-"*5
print item
c.close()
