Sarcasm detection on news headlines using transformers

Sarcasm detection on news headlines using transformers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sarcasm detection on news headlines using transformers Gizem Gümüşçekicci, Rahim Dehkharghani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6523727/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 22 You are reading this latest preprint version Abstract Sarcasm poses a linguistic challenge due to its figurative nature where intended meaning contradicts literal interpretation. Sarcasm is prevalent in human communication, affecting interactions in literature, social media, news, e-commerce, etc. Identifying the true intent behind sarcasm is challenging but essential for applications in sentiment analysis. Detecting sarcasm in written text is a challenging task, has attracted many researchers in recent years. This paper attempts to detect sarcasm in news headlines. Journalists prefer using sarcastic news headlines as they seem much more interesting for the readers. In the proposed methodology, we experimented with Transformers, namely the Bert model, and several Machine and Deep Learning models with different word and sentence embedding methods. We also extended an existing news headlines dataset for sarcasm detection using augmentation techniques and annotating it with hand-crafted features. The proposed methodology could outperform almost all existing sarcasm detection approaches with a 98.86% F1-score when applied to our extended news headlines dataset, which is publicly available on Github. Sarcasm News Headlines Sarcasm Classification Transformers Text Augmentation Handcrafted features Deep Learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 Jun, 2025 Reviews received at journal 06 Jun, 2025 Reviews received at journal 05 Jun, 2025 Reviews received at journal 04 Jun, 2025 Reviews received at journal 03 Jun, 2025 Reviewers agreed at journal 02 Jun, 2025 Reviews received at journal 01 Jun, 2025 Reviewers agreed at journal 01 Jun, 2025 Reviewers agreed at journal 31 May, 2025 Reviewers agreed at journal 31 May, 2025 Reviewers agreed at journal 30 May, 2025 Reviewers agreed at journal 29 May, 2025 Reviewers agreed at journal 29 May, 2025 Reviewers agreed at journal 28 May, 2025 Reviewers agreed at journal 28 May, 2025 Reviewers agreed at journal 28 May, 2025 Reviewers agreed at journal 28 May, 2025 Reviewers agreed at journal 28 May, 2025 Reviewers invited by journal 28 May, 2025 Editor assigned by journal 28 May, 2025 Submission checks completed at journal 26 Apr, 2025 First submitted to journal 24 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6523727","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":463604339,"identity":"2c83784f-5b62-4202-903a-98e58b4450cb","order_by":0,"name":"Gizem Gümüşçekicci","email":"","orcid":"","institution":"Işık University","correspondingAuthor":false,"prefix":"","firstName":"Gizem","middleName":"","lastName":"Gümüşçekicci","suffix":""},{"id":463604340,"identity":"8a2e9ca8-fed0-4b7c-9526-1a18b322d655","order_by":1,"name":"Rahim Dehkharghani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABL0lEQVRIie2RMUvDQBTHXwmkywtZE5T2K1w5aChF+lUiGboc0jGDxBShXWJmP0akk+CQ+sApoWsFB6GQqYsERKWISSsWSWodBfNb7t7d/fg/3gFUVPxJEEIACRhiXuV7iaTNlflrRba2SliuwHcFkP+oGON4ejuHbsPAeJrabw9No44pH5w6oNYFk55uCsphdGKSgD7vXPiWHvtJ6/pcmViXdwS6t2QQJgVFA8EyhY6DGTJ96FEtIGVCKIfA5iJTip1p6nKtnGUKf82UXkC4IHx3oLdL0TYpJou9tu6+ZHGEkqWMsoFou5Q8hfVbQRS1O0OXrIBkzhWfUIuSQRiVNSZ4Kuxuk0WC37srOgpmtDjAZ6ehjq2rR7tkymvY51obbc++vmkPq/1PKioqKv4fHx5UdJCHWTUTAAAAAElFTkSuQmCC","orcid":"","institution":"Kadir Has University","correspondingAuthor":true,"prefix":"","firstName":"Rahim","middleName":"","lastName":"Dehkharghani","suffix":""}],"badges":[],"createdAt":"2025-04-24 21:38:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6523727/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6523727/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83686541,"identity":"69ac2b91-2c80-4136-b583-2e82c709972d","added_by":"auto","created_at":"2025-05-30 18:23:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":840188,"visible":true,"origin":"","legend":"","description":"","filename":"SarcasmDetectionafterRejection.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6523727/v1_covered_9f6be587-5f77-43ae-b705-f60f4b6334b9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sarcasm detection on news headlines using transformers","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-journal-of-supercomputing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [The Journal of Supercomputing](https://www.springer.com/journal/11227)","snPcode":"11227","submissionUrl":"https://submission.nature.com/new-submission/11227/3","title":"The Journal of Supercomputing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Sarcasm, News Headlines, Sarcasm Classification, Transformers, Text Augmentation, Handcrafted features, Deep Learning","lastPublishedDoi":"10.21203/rs.3.rs-6523727/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6523727/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Sarcasm poses a linguistic challenge due to its figurative nature where intended meaning contradicts literal interpretation. 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