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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/avatars/d5fe48de11e46675b05e1e2e1cf3505c.svg
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.