  Parody is a figurative device used for mimicking entities for comedic or
critical purposes. Parody is intentionally humorous and often involves sarcasm.
This paper explores jointly modelling these figurative tropes with the goal of
improving performance of political parody detection in tweets. To this end, we
present a multi-encoder model that combines three parallel encoders to enrich
parody-specific representations with humor and sarcasm information. Experiments
on a publicly available data set of political parody tweets demonstrate that
our approach outperforms previous state-of-the-art methods.
