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Using Classifier Features for Studying the Effect of Native Language on the Choice of Written Second Language Words

By Oren Tsur

Abstract

We apply modern statistical NLP techniques to study language transfer, a major issue in the theory of Second Language Acquisition (SLA). Using an SVM for the problem of native language classification, we show that a careful analysis of the effects of various features can lead to substantial scientific insights. In particular, we demonstrate that character bi-grams alone allow classification levels of about 66 % for a 5-class task even when content and function word differences are accounted for. We hypothesize that the phonology of a native language has a strong effect on the word choice of people writing in a second language.

Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.9754
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