import sentiment
import json
# sentiment.analyse expects a list of (review string, rating) tuples.
# This example uses academic dataset https://www.yelp.com/academic_dataset
# It's around 200 mb so I won't be uploading it to github.
labMTPath = "happiness.txt"
yelp = "..\Yelp\yelp_phoenix_academic_dataset\yelp_academic_dataset_review.json"
def loadYelpData(path):
reviews = []
with open(path, "r") as f:
for line in f:
dict = json.loads(line)
reviews += [(dict["text"], float(dict["stars"]))]
return reviews
sentiment.analyse(loadYelpData(yelp), labMTPath, "yelpSentiment.pkl")
sentiment.visualise("yelpSentiment.pkl")
# sentiment.analyse expects a list of (review string, rating) tuples.
# This example uses academic dataset https://www.yelp.com/academic_dataset
# It's around 200 mb so I won't be uploading it to github.
labMTPath = "happiness.txt"
grPath = "../../data/goodreads.20130510.txt"
def loadYelpData(path):
reviews = []
with open(path, "r") as f:
for line in f:
dict = json.loads(line)
reviews += [(dict["text"], float(dict["stars"]))]
return reviews
def loadGoodreadsData(path):
reviews = []
input_ = open(path, "rb")
data = pickle.load(input_)
for i in range(len(data["stars"])):
reviews += [(data["reviews"][i], data["stars"][i])]
return reviews
data = loadGoodreadsData(grPath)
#print data
sentiment.analyse(data, labMTPath, "goodreadsSentiment.pkl")
sentiment.visualise('goodreadsSentiment.pkl')
