Introducing the Greek Humorous Dataset: A benchmark for Computational Humor Recognition

Introducing the Greek Humorous Dataset: A benchmark for Computational Humor Recognition | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 18 February 2025 V1 Latest version Share on Introducing the Greek Humorous Dataset: A benchmark for Computational Humor Recognition Authors : Antonios Kalloniatis [email protected] and Panagiotis Adamidis Authors Info & Affiliations https://doi.org/10.22541/au.173988240.06858837/v1 246 views 147 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Computational humor recognition is considered one of the most challenging tasks in Natural Language Processing (NLP) primarily due to the intricate nature of humor as an emotion. Although most studies on humor recognition have focused on English textual sources, much work has been done in other languages as well. However, there is a notable gap in the literature concerning the Greek language. This paper introduces the first-ever Greek Humorous Dataset (GHD), specifically designed to address this void in the literature. GHD is a manually annotated balanced dataset consisting of 10,000 short text samples labeled as either humorous or non-humorous. In addition to a detailed description of the dataset, we compare the performance of ten machine learning models using text representation feature engineering techniques to establish benchmarks for future research. With the development of GHD, we aim to not only contribute to the expanding field of knowledge in computational humor recognition but also foster a positive impact on future research endeavors in Greek language processing. Supplementary Material File (akalloniatis.docx) Download 102.95 KB Information & Authors Information Version history V1 Version 1 18 February 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence computational humor recognition greek humorous dataset natural language processing text classification Authors Affiliations Antonios Kalloniatis [email protected] International Hellenic University View all articles by this author Panagiotis Adamidis International Hellenic University View all articles by this author Metrics & Citations Metrics Article Usage 246 views 147 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Antonios Kalloniatis, Panagiotis Adamidis. Introducing the Greek Humorous Dataset: A benchmark for Computational Humor Recognition. Authorea . 18 February 2025. DOI: https://doi.org/10.22541/au.173988240.06858837/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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