Weighting of words in lexicon based sentiment analysis
Yes, you can. Not quite sure what else to add. Your formula can then look like:

$$ Score = \sum_{i}{f(salience_i, frequency_i, sentiment_i)}$$

Where $f$ is a function that weighs your sentiment score with the salience and frequency. Up to you to define how.


What if you don't know which $f$ to use?


Now, bear with me, this isn't something I've tried per se, but this could be an interesting approach. You could use a recurrent neural network and your input could be the salience, frequency, and sentiment score for each word. Not only will your RNN "create" (ideally) the best $f$ for your particular problem, but it will also use the sequential information of the words, which may even improve your results.