#Create a Keyword Sentiment Analyzer #Tokenize your documents using the Stanford CoreNLP or Apache OpenNLP package ( See NLP. R on Moodle ) #Create a function called "sentiment (doc )" that takes a documents as it's input and returns a sentiment score by summing the number of positive and negative words in a document. The final score=number_of_positive_words - number_of_negative_words. #Useful functions for this lab: #tokenizedwords %in% positivewordlist : This line will check the individual words membership in the positivewordlist variable. It returns a boolean vector. #which (booleanvector ) : This function returns the vector locations with TRUE values in a boolean vector #length (vectorlocations) : This function returns the number of elements in a vector #Come up with some documents of your own to test doc