Commonality and Individuality! Integrating Humor Commonality with Speaker Individuality for Humor Recognition
Haohao Zhu, Xiaokun Zhang, Zeyuan Zeng, Junyu Lu, Zewen Bai, Liang Yang, Hongfei Lin
Abstract
Humor recognition aims to identify whether a specific speaker’s text is humorous. Current methods for humor recognition mainly suffer from two limitations: (1) they solely focus on one aspect of humor commonalities, ignoring the multifaceted nature of humor; and (2) they typically overlook the critical role of speaker individuality, which is essential for a comprehensive understanding of humor expressions. To bridge these gaps, we introduce the Commonality and Individuality Incorporated Network for Humor Recognition (CIHR), a novel model designed to enhance humor recognition by integrating multifaceted humor commonalities with the distinctive individuality of speakers. The CIHR features a Humor Commonality Analysis module that explores various perspectives of multifaceted humor commonality within user texts, and a Speaker Individuality Extraction module that captures both static and dynamic aspects of a speaker’s profile to accurately model their distinctive individuality. Additionally, Static and Dynamic Fusion modules are introduced to effectively incorporate the humor commonality with speaker’s individuality in the humor recognition process. Extensive experiments demonstrate the effectiveness of CIHR, underscoring the importance of concurrently addressing both multifaceted humor commonality and distinctive speaker individuality in humor recognition.
BibTeX
@inproceedings{zhu-etal-2025-commonality,
title = "Commonality and Individuality! Integrating Humor Commonality with Speaker Individuality for Humor Recognition",
author = "Zhu, Haohao and
Zhang, Xiaokun and
Zeng, Zeyuan and
Lu, Junyu and
Bai, Zewen and
Yang, Liang and
Lin, Hongfei",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-long.385/",
pages = "7535--7547",
ISBN = "979-8-89176-189-6"
}