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')