Predicting Code-switching in Multilingual Communication for Immigrant Communities
نویسندگان
چکیده
Immigrant communities host multilingual speakers who switch across languages and cultures in their daily communication practices. Although there are in-depth linguistic descriptions of code-switching across different multilingual communication settings, there is a need for automatic prediction of code-switching in large datasets. We use emoticons and multi-word expressions as novel features to predict code-switching in a large online discussion forum for the Turkish-Dutch immigrant community in the Netherlands. Our results indicate that multi-word expressions are powerful features to predict code-switching.
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تاریخ انتشار 2014