1. A system for providing a language classification of a media item, comprising: a context classifier to determine a context characteristic indicating one or more users who have interacted with the media item; wherein the context characteristic corresponds to a computed likelihood that the media item is in one or more languages based on determined language abilities of the users who have interacted with the media item; the context classifier to compute, based on the determined context characteristic and corresponding computed likelihood, a context prediction that the media item is in one or more first languages; a trained classifier to compute a trained prediction that the media item is in one or more second languages; wherein the trained n-gram analysis of the media item comprises, for one or more n-grams in the media item having a particular length, analyzing a specified probability distribution that the n-gram is in a specific language; and a language classifier to combine the context prediction with the trained prediction.