Fuzzy rule based multi class sentiment analysis using hybrid nature inspired machine learning technique

Fuzzy rule based multi class sentiment analysis using hybrid nature inspired machine learning technique | 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 Fuzzy rule based multi class sentiment analysis using hybrid nature inspired machine learning technique Abinash Tripathy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6859329/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 20 You are reading this latest preprint version Abstract Due to the increased availability of the Internet and various social media, the sharing of views or comments about any issue has increased. These reviews act as an important resource for understanding the feelings of customers and concerns related to the product and thus, need to be processed properly. Sentiment analysis plays a vital role in processing the reviews and obtaining information that can be used further. Many authors prefer to perform the binary sentiment task by classifying the reviews into either negative or positive classes. The present paper chooses multi-class classification, where the reviews are classified into five different classes. To perform the binary classification task, two sets of hybrid nature-inspired techniques are used i.e., firstly Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN); and secondly, Flower Pollination Algorithm (FPA) and Artificial Neural Network (ANN). PSO and FPA are used for feature selection and ANN then processes the selected features for binary classification. The reviews that are classified correctly go through a Fuzzy rule-based system for multi-class classification. For classification purposes, two movie review datasets namely, IMDb and Polarity dataset are considered. Multi-class sentiment classification Particle Swarm Optimization (PSO) Flower Pollination Algorithm (FPA) Artificial Neural Network (ANN) IMDb dataset Polarity dataset Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 31 Aug, 2025 Reviews received at journal 18 Jul, 2025 Reviews received at journal 17 Jul, 2025 Reviews received at journal 07 Jul, 2025 Reviews received at journal 03 Jul, 2025 Reviews received at journal 24 Jun, 2025 Reviewers agreed at journal 24 Jun, 2025 Reviews received at journal 22 Jun, 2025 Reviewers agreed at journal 22 Jun, 2025 Reviewers agreed at journal 19 Jun, 2025 Reviewers agreed at journal 19 Jun, 2025 Reviews received at journal 18 Jun, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers invited by journal 17 Jun, 2025 Editor assigned by journal 17 Jun, 2025 Submission checks completed at journal 16 Jun, 2025 First submitted to journal 10 Jun, 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-6859329","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":472899543,"identity":"119061e9-c13d-4a3b-968c-927dab8593b2","order_by":0,"name":"Abinash Tripathy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYDACCcYGEAnEPAwMH4AUGzsxWg6AtLDxMDDOAGlhJqgFiA+AGEAtzDwgBiEt/LObG5g/7rHI45/fe0za5tc2eT5mBsYPH3PwWHLnINBhzySKJY7xpUnn9t02bGNmYJacuQ2PNTcSgVoOSCQ2HOMxk87tuc0I1MLGzItHizxMy3yQFsue2/YEtRjAtGwAaWH4cTuRoBZDoF8OnDkgUWx4LMfYsrfhdnIbM2MzXr/I3W5/+KDiQF2e3OEzhjd+/LltO7+9+eCHj/i8zwCJlgQgZpFgbAPxwemBMABpYf7A8IcoxaNgFIyCUTDCAAAeaVQmZCXMbAAAAABJRU5ErkJggg==","orcid":"","institution":"Kalinga Institute of Industrial Technology (KIIT) Deemed to be University","correspondingAuthor":true,"prefix":"","firstName":"Abinash","middleName":"","lastName":"Tripathy","suffix":""}],"badges":[],"createdAt":"2025-06-10 06:01:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6859329/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6859329/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85002187,"identity":"8d459667-2a77-442b-8fbc-6d400bdcbd7e","added_by":"auto","created_at":"2025-06-19 18:22:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":692282,"visible":true,"origin":"","legend":"","description":"","filename":"snarticle.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6859329/v1_covered_2bf97f4b-3b73-4a86-9167-f9e1c039cbd8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Fuzzy rule based multi class sentiment analysis using hybrid nature inspired machine learning technique","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":"international-journal-of-machine-learning-and-cybernetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmlc","sideBox":"Learn more about [International Journal of Machine Learning and Cybernetics](http://actavetscand.biomedcentral.com/)","snPcode":"13042","submissionUrl":"https://submission.nature.com/new-submission/13042/3","title":"International Journal of Machine Learning and Cybernetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Multi-class sentiment classification, Particle Swarm Optimization (PSO), Flower Pollination Algorithm (FPA), Artificial Neural Network (ANN), IMDb dataset, Polarity dataset","lastPublishedDoi":"10.21203/rs.3.rs-6859329/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6859329/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Due to the increased availability of the Internet and various social media, the sharing of views or comments about any issue has increased. 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