Discriminating between similar languages in Twitter using label propagation

Identifying the language of social media messages is an important first step in linguistic processing. Existing models for Twitter focus on content analysis, which is successful for dissimilar language pairs. We propose a label propagation approach that takes the social graph of tweet authors into a...

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Bibliographic Details
Published inarXiv.org
Main Authors Radford, Will, Galle, Matthias
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 19.07.2016
Subjects
Content analysis
Digital media
Languages
Propagation
Social networks
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Summary:Identifying the language of social media messages is an important first step in linguistic processing. Existing models for Twitter focus on content analysis, which is successful for dissimilar language pairs. We propose a label propagation approach that takes the social graph of tweet authors into account as well as content to better tease apart similar languages. This results in state-of-the-art shared task performance of \(76.63\%\), \(1.4\%\) higher than the top system.
ISSN:2331-8422