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Identifying the language of social media messages is an important first stepin linguistic processing. Existing models for Twitter focus on contentanalysis, which is successful for dissimilar language pairs. We propose a labelpropagation approach that takes the social graph of tweet authors into accountas well as content to better tease apart similar languages. This results instate-of-the-art shared task performance of $76.63\%$, $1.4\%$ higher than thetop system.

Discriminating between similar languages in Twitter using label propagation