Deceptive Humor: A Synthetic Multilingual Benchmark Dataset for Bridging
  Fabricated Claims with Humorous Content
This paper presents the Deceptive Humor Dataset (DHD), a novel resource for
studying humor derived from fabricated claims and misinformation. In an era of
rampant misinformation, understanding how humor intertwines with deception is
essential. DHD consists of humor-infused comments generated from false
narratives, incorporating fabricated claims and manipulated information using
the ChatGPT-4o model. Each instance is labeled with a Satire Level, ranging
from 1 for subtle satire to 3 for high-level satire and classified into five
distinct Humor Categories: Dark Humor, Irony, Social Commentary, Wordplay, and
Absurdity. The dataset spans multiple languages including English, Telugu,
Hindi, Kannada, Tamil, and their code-mixed variants (Te-En, Hi-En, Ka-En,
Ta-En), making it a valuable multilingual benchmark. By introducing DHD, we
establish a structured foundation for analyzing humor in deceptive contexts,
paving the way for a new research direction that explores how humor not only
interacts with misinformation but also influences its perception and spread. We
establish strong baselines for the proposed dataset, providing a foundation for
future research to benchmark and advance deceptive humor detection models.
67dcc5e41f94b594ef4c0312
Sai Kartheek Reddy Kasu
extracted_confirmed
2025-03-21T01:51:18.039Z
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Sai Kartheek Reddy
user
UVSKKR
67dcc5e41f94b594ef4c0313
Shankar Biradar
admin_assigned
2025-03-21T13:11:38.661Z
6443c91b79e7797ce719dbaf
/avatars/5c981c39075b35cc0ea69bf0253829a0.svg
shankar Biradar
user
shankarB
67dcc5e41f94b594ef4c0314
Sunil Saumya
Deceptive Humor: A Synthetic Multilingual Benchmark Dataset for Bridging
  Fabricated Claims with Humorous Content
This paper presents the Deceptive Humor Dataset (DHD), a novel resource for
studying humor derived from fabricated claims and misinformation. In an era of
rampant misinformation, understanding how humor intertwines with deception is
essential. DHD consists of humor-infused comments generated from false
narratives, incorporating fabricated claims and manipulated information using
the ChatGPT-4o model. Each instance is labeled with a Satire Level, ranging
from 1 for subtle satire to 3 for high-level satire and classified into five
distinct Humor Categories: Dark Humor, Irony, Social Commentary, Wordplay, and
Absurdity. The dataset spans multiple languages including English, Telugu,
Hindi, Kannada, Tamil, and their code-mixed variants (Te-En, Hi-En, Ka-En,
Ta-En), making it a valuable multilingual benchmark. By introducing DHD, we
establish a structured foundation for analyzing humor in deceptive contexts,
paving the way for a new research direction that explores how humor not only
interacts with misinformation but also influences its perception and spread. We
establish strong baselines for the proposed dataset, providing a foundation for
future research to benchmark and advance deceptive humor detection models.
The Deceptive Humor Dataset, a multilingual benchmark, provides a resource for studying humor in fabricated claims and misinformation, with classifications for satire levels and humor categories, facilitating the analysis of how humor interacts with deceptive content.
Deceptive Humor Dataset ChatGPT-4o Satire Level Humor Categories Dark Humor Irony Social Commentary Wordplay Absurdity multilingual benchmark deceptive humor detection models