4 papers with code • 1 benchmarks • 2 datasets
Native Language Identification (NLI) is the task of determining an author's native language (L1) based only on their writings in a second language (L2).
Despite impressive performance on many text classification tasks, deep neural networks tend to learn frequent superficial patterns that are specific to the training data and do not always generalize well.
It can be used for training machine learning based systems for classifying and identifying the native language of authors of English text.
The detection of clandestine efforts to influence users in online communities is a challenging problem with significant active development.
We report on our experiments with N-gram and embedding based feature representations for Native Language Identification (NLI) as a part of the NLI Shared Task 2017 (team name: NLI-ISU).
Ranked #2 on Native Language Identification on italki NLI