anchor.diff:      neg_emoji = [u'😞', u'😠', u'😩', u'😢', u'😭', u'😒'] # negative emoji
   
       # add patterns to match one or more emoji tokens
  -    pos_patterns = [[{'ORTH': emoji, 'OP': '+'}] for emoji in pos_emoji]
  -    neg_patterns = [[{'ORTH': emoji, 'OP': '+'}] for emoji in neg_emoji]
  +    pos_patterns = [[{'ORTH': emoji}] for emoji in pos_emoji]
  +    neg_patterns = [[{'ORTH': emoji}] for emoji in neg_emoji]
   
       matcher.add('HAPPY', label_sentiment, *pos_patterns) # add positive pattern
       matcher.add('SAD', label_sentiment, *neg_patterns) # add negative pattern
  
positive.code: 
  p
      |  By default, spaCy's tokenizer will split emoji into separate tokens. This
      |  means that you can create a pattern for one or more emoji tokens. In this
      |  case, a sequence of identical emoji should be treated as one instance.
      |  Valid hashtags usually consist of a #[code #], plus a sequence of
      |  ASCII characters with no whitespace, making them easy to match as well.
  
  
negative.code: 
      def label_sentiment(matcher, doc, i, matches):
          match_id, start, end = matches[i]
          if doc.vocab.strings[match_id] == 'HAPPY': # don't forget to get string!
              doc.sentiment += 0.1 # add 0.1 for positive sentiment
          elif doc.vocab.strings[match_id] == 'SAD':
              doc.sentiment -= 0.1 # subtract 0.1 for negative sentiment
          span = doc[start : end]
          emoji = Emojipedia.search(span[0].text) # get data for emoji
  