NLP classify sentences/paragraph as funny

Question

Is there a way to classify a particular sentence/paragraph as funny. There are very few pointers as to where one should go further on this.

Answer 1

The only way to pull this off is to get a couple of thousand people (monkeys won't do, sorry) to look through thousands of funny sentences/stories, rate them, and then build some sort of expert system/neural network out of it. Given the problem scope and the subjectivity of it (a thing funny to one person might not be funny - even offensive - to another), I'd say it's an impossible task.

Answer 2

Yes, you should use a Training Corpora to build a predictive model able to detect funny sentences. Sometimes this is known as "Sentiment Analysis" in the literature. Take a look at this article about Sentiment Analysis with LingPipe.

If you can use Java, you can use their library (see license matrix). I found it very useful, not exactly in the same context than you.

Answer 3

There is research on this, it's called Computational Humor. It's an interdisciplinary area that takes elements from computational linguistics, psycholinguistics, artificial intelligence, machine learning etc. They are trying to find out what it is that makes stories or jokes funny (e.g. the unexpected connection, or using a taboo topic in a surprising way etc) and apply it to text (either to generate a funny story or to measure the 'funniness' of text).

There are books and articles about it (e.g. by Graeme Ritchie).

Answer 4

You can use the same technique as spam filters. Instead of spam/non-spam you classify on funny/not-funny. Look into naive bayesian classifiers for more information.

http://en.wikipedia.org/wiki/Naive_Bayesian_classification

Answer 5

Also, try Computational Humor @ Google Scholar if you're serious about getting into the field. Sentiment Analysis has been mentioned too, see wikipedia on that.

Of course, this all depends on what your scope and aims are...