gistfile1.txt

pos.words = scan(file.path('opinion-lexicon-English', 'positive-words.txt'), what='character', comment.char=';')
neg.words = scan(file.path('opinion-lexicon-English', 'negative-words.txt'), what='character', comment.char=';')

score.sentiment = function(sentences, pos.words, neg.words, .progress='none') {

    # we got a vector of sentences. plyr will handle a list or a vector as an "l" for us
    scores = laply(sentences, function(sentence, pos.words, neg.words) {
        
        # clean up sentences with R's regex-driven global substitute, gsub():
        sentence = gsub('[[:punct:]]', '', sentence)
        sentence = gsub('[[:cntrl:]]', '', sentence)
        sentence = gsub('\\d+', '', sentence)
        # and convert to lower case:
        sentence = tolower(sentence)
        
        # split into words
        word.list = str_split(sentence, '\\s+')
        # sometimes a list() is one level of hierarchy too much
        words = unlist(word.list)
        
        # compare our words to the dictionaries of positive & negative lexicons
        pos.matches = match(words, pos.words)
        neg.matches = match(words, neg.words)
        
        # we just want a TRUE/FALSE:
        pos.matches = !is.na(pos.matches)
        neg.matches = !is.na(neg.matches)
        
        # TRUE/FALSE will be treated as 1/0 by sum():
        score = sum(pos.matches) - sum(neg.matches)
        
        return(score)
    }, pos.words, neg.words, .progress=.progress )
    
    scores.df = data.frame(score=scores, text=sentences)
    return(scores.df)
}