  Automatic language identification is a natural language processing problem
that tries to determine the natural language of a given content. In this paper
we present a statistical method for automatic language identification of
written text using dictionaries containing stop words and diacritics. We
propose different approaches that combine the two dictionaries to accurately
determine the language of textual corpora. This method was chosen because stop
words and diacritics are very specific to a language, although some languages
have some similar words and special characters they are not all common. The
languages taken into account were romance languages because they are very
similar and usually it is hard to distinguish between them from a computational
point of view. We have tested our method using a Twitter corpus and a news
article corpus. Both corpora consists of UTF-8 encoded text, so the diacritics
could be taken into account, in the case that the text has no diacritics only
the stop words are used to determine the language of the text. The experimental
results show that the proposed method has an accuracy of over 90% for small
texts and over 99.8% for
