Combining Humor and Sarcasm for Improving Political Parody Detection
This work addresses the challenge of identifying parody in political tweets, which is important for media analysis and misinformation detection, but it appears incremental as it builds on existing methods by incorporating additional figurative tropes.
The paper tackled the problem of detecting political parody in tweets by jointly modeling humor and sarcasm, resulting in a multi-encoder model that outperformed previous state-of-the-art methods on a public dataset.
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.