欺骗性幽默：一个用于桥接虚构声明与幽默内容的多语言合成基准数据集

Deceptive Humor: A Synthetic Multilingual Benchmark Dataset for Bridging Fabricated Claims with Humorous Content

March 20, 2025

作者: Sai Kartheek Reddy Kasu, Shankar Biradar, Sunil Saumya

cs.AI

摘要

本文介绍了欺骗性幽默数据集（Deceptive Humor Dataset, DHD），这是一个用于研究源自虚假声明和误导信息的幽默的新型资源。在虚假信息泛滥的时代，理解幽默如何与欺骗交织至关重要。DHD包含由ChatGPT-4o模型生成的基于虚假叙事的幽默评论，这些评论融入了捏造的声明和操纵的信息。每个实例都标注了讽刺等级，从1级（微妙讽刺）到3级（高度讽刺），并分为五个不同的幽默类别：黑色幽默、讽刺、社会评论、文字游戏和荒诞。该数据集涵盖多种语言，包括英语、泰卢固语、印地语、卡纳达语、泰米尔语及其混合语言变体（Te-En、Hi-En、Ka-En、Ta-En），使其成为一个宝贵的多语言基准。通过引入DHD，我们为分析欺骗性语境中的幽默建立了一个结构化基础，为探索幽默不仅与误导信息互动，还影响其感知和传播的新研究方向铺平了道路。我们为该数据集建立了强大的基线，为未来研究提供了基准，并推动了欺骗性幽默检测模型的发展。

English

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.