title: Match stock tickers in the text with a list of stock tickers without matching the stop words
body: <p>I have a python list with around 28,000 stock tickers.</p>
  <p>I'm parsing through text which I scraped to match with the stock tickers and increase the count whenever I get a match.</p>
  <p>The issue I am having is all the stop words are matching with some of the tickers which I don't want; eg V is a legitimate ticker and is matching with the individual tokenized words as it is free flowing social media text. eg V want TSLA.</p>
  <p>Could you suggest me some logic where I could apply some logical smart matching with using these stop words?</p>
  <pre><code>counts = dict()
  Symbol_list =['TSLA','V','T','AAPL',...]
  
  example sentence = { 'V want TSLA but not. T + 5 times' } 
  </code></pre>
  <p>This is what I've tried so far:</p>
  <pre><code>sen = example_sentence.translate(str.maketrans('','',string.punctuation))
  
  sentence_words = sen.split()
  for words in sentence_words:
      if(word in symbol_list):
          counts[word] = counts.get(word,0) + 1
  </code></pre>
  <p>I would like to have <code>{'TSLA':1}</code> but not <code>{'TSLA':1, 'V':1, 'T': 1}</code>.
  There might be some instances where I might need T and V to be added to the dictionary but contextually.</p>