def analyze_statement(self): """Analyzes the douchiness of the words in statment.""" self.extract_words(self.string) counter = 0 score = 0 for word in self.word_list: if word_sentiments.get(word) != None: score += word_sentiments.get(word) counter += 1 if counter != 0: self.total_douchiness += score/counter
def analyze_tweet_sentiment(tweet): """ Return a sentiment representing the degree of positive or negative sentiment in the given tweet, averaging over all the words in the tweet that have a sentiment value. If no words in the tweet have a sentiment value, return make_sentiment(None). >>> positive = make_tweet('i love my job. #winning', None, 0, 0) >>> round(sentiment_value(analyze_tweet_sentiment(positive)), 5) 0.29167 >>> negative = make_tweet("saying, 'i hate my job'", None, 0, 0) >>> sentiment_value(analyze_tweet_sentiment(negative)) -0.25 >>> no_sentiment = make_tweet("berkeley golden bears!", None, 0, 0) >>> has_sentiment(analyze_tweet_sentiment(no_sentiment)) False """ # You may change any of the lines below. words = tweet_words(tweet) net_sent = 0.0 count = 0 for i in range(0,len(words)): curr_sent = make_sentiment(word_sentiments.get(words[i])) if has_sentiment(curr_sent): sent_val = sentiment_value(curr_sent) if type(curr_sent == float): count += 1 net_sent += sent_val if count > 0: return make_sentiment(net_sent/count) return make_sentiment(None)
def get_word_sentiment(word): """Return a sentiment representing the degree of positive or negative feeling in the given word, if word is not in the sentiment dictionary. >>> sentiment_value(get_word_sentiment('good')) 0.875 >>> sentiment_value(get_word_sentiment('bad')) -0.625 >>> sentiment_value(get_word_sentiment('winning')) 0.5 >>> has_sentiment(get_word_sentiment('Berkeley')) False """ return make_sentiment(word_sentiments.get(word, None))
def get_word_sentiment(word): """Return a sentiment representing the degree of positive or negative feeling in the given word. >>> sentiment_value(get_word_sentiment('good')) 0.875 >>> sentiment_value(get_word_sentiment('bad')) -0.625 >>> sentiment_value(get_word_sentiment('winning')) 0.5 >>> has_sentiment(get_word_sentiment('Berkeley')) False """ return make_sentiment(word_sentiments.get(word, None))
def get_word_sentiment(word): """Return a sentiment representing the degree of positive or negative feeling in the given word. >>> sentiment_value(get_word_sentiment('good')) 0.875 >>> sentiment_value(get_word_sentiment('bad')) -0.625 >>> sentiment_value(get_word_sentiment('winning')) 0.5 >>> has_sentiment(get_word_sentiment('Berkeley')) False """ # Learn more: http://docs.python.org/3/library/stdtypes.html#dict.get return make_sentiment(word_sentiments.get(word))
def get_word_sentiment(word): """Return a number between -1 and +1 representing the degree of positive or negative feeling in the given word. Return None if the word is not in the sentiment dictionary. (0 represents a neutral feeling, not an unknown feeling.) >>> get_word_sentiment('good') 0.875 >>> get_word_sentiment('bad') -0.625 >>> get_word_sentiment('winning') 0.5 >>> get_word_sentiment('Berkeley') # Returns None """ return word_sentiments.get(word, None)
def get_word_sentiment(word): return make_sentiment(word_sentiments.get(word))