parser.add_argument("-v", "--verbose", help = "Print traces for debugging", type=bool, default=False)
### End of arguments ###
####main####
args = parser.parse_args()
tClient = TwitterClient()
ReviewRules = [('VeryGood' , 90),
('Good' , 80),
('Watchable', 70),
('Average' , 60),
('Bad' , 30),
('VeryBad' , 0)]
multi_search_results = tClient.multi_search_until(k=args.Movie, ud=args.since_date, verbose=args.verbose)
total_tweets, opinion_dictionary = tClient.review_mining_multi(multi_search_results, ReviewRules)
'''
opinion dictionary is a dictionary of dictionaries has the following structure
{Sentiment : {tweet_id: tweet_text}}
ex: {'VeryGood' : { 1 : "Must Watch",
2 : "Top Notch" } }
'''
result_summary_dictionary = OrderedDict({int: [str,(float, int)]})
'''
{SentimentSNo:[Sentiment,
(approved percetage(percentage of tweets who approved this rating),
tweets in rating(number of tweets in rating)
