Consider the following statements
We are not talking about a well established company in the NASDAQ I will not initiate any trades until those clowns hammer out a deal
I am writing a simple Naive Bayes classifier, basically marking a training set of statements by hand (as either positive or negative sentiment) and storing the words that make up the statement accordingly.
Problem: if I mark both of these statements as having a negative sentiment, the words "well", "established" (statement 1) and "any", "until" (statement 2) would be indivudually marked as negatives. Whereas in another case (i.e., "This company is performing well"), the same words ("well" in this case) would be marked as a positive, making the sum of sentiment for "well" -1 + 1 = 0. I would overcome this by tagging these words as negated words, for example:
We are talking about a not-well not-established company in the NASDAY. I will initiate not-anymore trades not-until those clowns hammer out a deal
Is there a standard or best way of tagging these kinds of words (I don't even know if they are of a same group of words)? Obviously, tagging "company" wouldn't make sense "not-company" doesn't hold any sentimental value. I have (in PHP) made a function that would tag all words after the negation word (not, no, couldn't, etc) but many of them didn't make real sense afterwards (such as "not-company", "not-NASDAQ", "not-clowns").
Since English is not my mother language, I'm asking you if there's a common name for the words I have marked here and if what I want is (rudimentary) possible. I am aware that there are a lot of exceptions possible (double negations etc.) but I do not want to go into that; I believe if this would be possible, it would cover a lot of ground.