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)