A Language Identification Method Applied to Twitter Data

This paper presents the results of some experiments on using a simple algorithm, aided by a few heuristics, for the purposes of language identification on Twitter data. These experiments were a part of a shared task focused on this problem. The core algorithm is an n-gram based distance metric algorithm. This algorithm has previously been shown to work very well on normal text. The distance metric used is symmetric cross entropy.