Native Language Identification with User Generated Content

被引：0
|
作者：
Goldin, Gili [1 ]
Rabinovich, Ella [2 ,3 ]
Wintner, Shuly [1 ]
机构：
[1] Univ Haifa, Dept Comp Sci, Haifa, Israel
[2] Univ Toronto, Dept Comp Sci, Toronto, ON, Canada
[3] Univ Haifa, Haifa, Israel
来源：
2018 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING (EMNLP 2018) | 2018年
基金：
美国国家科学基金会;
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We address the task of native language identification in the context of social media content, where authors are highly-fluent, advanced nonnative speakers (of English). Using both linguistically-motivated features and the characteristics of the social media outlet, we obtain high accuracy on this challenging task. We provide a detailed analysis of the features that sheds light on differences between native and nonnative speakers, and among nonnative speakers with different backgrounds.
引用
收藏
页码：3591 / 3601
页数：11
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