How to train Stanford CoreNLP for other language sentiments?

Question

I am using CoreNLP to calculate sentiment of given text. I have successfully executed it for English. I need to do the same for other languages like Hindi. May I please know how to train the system and use it for other languages? Below is the code for English:

Properties props = new Properties();
props.setProperty("annotators", "tokenize, ssplit, parse, sentiment");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
String text = "I love the display of iPhone but hate its battery life";
Annotation annotation = pipeline.process(text);
for (CoreMap sentence : annotation.get(CoreAnnotations.SentencesAnnotation.class)) {
   Tree tree = sentence.get(SentimentCoreAnnotations.AnnotatedTree.class);
   int sentiment = RNNCoreAnnotations.getPredictedClass(tree);
   System.out.println(sentiment);
}                

Answer 1

Information on training Stanford NLP RNTN is provided by mbatchkarov .

In general, non-English Sentiment Analysis is still a work in progress and many methods - especially those that go beyond bag-of-words - may need to be substantially rethought in order to be applicable to another language. For example, aggulutinative languages like Turkish or German (ie languages that crunch a lot of words into one big word) aren't even going to jive that well on a number of text-mining and sentiment analysis tasks.

Try googling sentiment analysis for Hindi. One interesting paper I found was this one by Mittal, et al .