def parseReviews(review_filepath):
f_in = open(review_filepath, 'r')
f_out = open ("out.csv", "w")
csv_writer = csv.writer(f_out)
count = 0
sentiment_analyzer = Sentiment()
for review in f_in:
count+=1
if count % 1000 == 0:
print(count)
review_obj = json.loads(review)
text = review_obj["text"]
date = review_obj["date"]
votes = review_obj["votes"]
stars = review_obj["stars"]
funny = votes["funny"]
useful = votes["useful"]
cool = votes["cool"]
year = int(date.split("-")[0])
normalize_factor = float(2016-year)/time_normalize_factor
funny_norm = float(funny/normalize_factor)
useful_norm = float(useful/normalize_factor)
cool_norm = float(cool/normalize_factor)
sentiment = sentiment_analyzer.getSentiment(text)
csv_writer.writerow([sentiment, funny, useful, cool, funny_norm, useful_norm, cool_norm, stars])
f_in.close()
f_out.close()
from bs4 import BeautifulSoup
import os
from sentiment import Sentiment
import csv
if __name__ == '__main__':
files = os.listdir('./zagat')
csvFile = open('out.csv','w')
writer = csv.writer(csvFile)
sentiment = Sentiment()
for f in files:
with open('./zagat/'+f) as review:
soup = BeautifulSoup(review)
review_city = soup.find(itemprop='addressLocality').text
review_state = soup.find(itemprop='addressRegion').text
review_text = soup.find(itemprop='reviewBody').text
review_sent = sentiment.getSentiment(review_text)
writer.writerow([str(review_sent),review_state,review_city])
close(csvFile)
