In short: For naive Bayes and text classification, do you multiply a probability for each instance of a word in a document or once if the word occurs?
In more detail: The question is how to calculate naive Bayes for a document. We have a corpus of text from which we can calculate the frequency of documents with class $C$ having a word $w$. We then calculate the probability $P(w_1|C)...P(w_n|C)$ and choose the $C$ that maximizes this number. But I'm not sure whether we multiply a probability for each word whenever it occurs or just once if it occurs in the document? Like, if the text is "$w_1 \ w_2 \ w_1$", is the estimated probability $P(w_1|C)^2 P(w_2|C)$ or is it $P(w_1|C)P(w_2|C)$?