The humorous data set consists of one-liners collected from the Web using an automatic bootstrapping process.
we investigate whether automatic classification techniques are a viable approach to distinguish between humorous and non-humorous text, and we bring empirical evidence in support of this hypothesis through experiments performed on very large data sets.