10. A method, implemented by a computing system comprising one or more processors, the method comprising: providing, using one or more of the processors, a corpus in a language by non-native users of the language; measuring, using one or more of the processors, characteristics of the corpus; using the characteristics to create, using one or more of the processors, a classifier for indicating non-native usage of the language; receiving an input, and using the classifier on the input for indicating non-native usage; adding the input indicated as non-native usage to the corpus; re-measuring the characteristics of the corpus; and using the re-measured characteristics to create a refined classifier for indicating non-native usage of the language; in which at least one of the first classifier and the refined classifier is prepared by a classification algorithm that comprises a support vector machine.
10. A method, implemented by a computing system comprising one or more processors, the method comprising: providing, using one or more of the processors, a corpus in a language by non-native users of the language; measuring, using one or more of the processors, characteristics of the corpus; using the characteristics to create, using one or more of the processors, a classifier for indicating non-native usage of the language; receiving an input, and using the classifier on the input for indicating non-native usage; adding the input indicated as non-native usage to the corpus; re-measuring the characteristics of the corpus; and using the re-measured characteristics to create a refined classifier for indicating non-native usage of the language; in which at least one of the first classifier and the refined classifier is prepared by a classification algorithm that comprises a support vector machine. 15. The method of claim 10 , wherein the characteristics measured comprise lexical N-gram features.