Examine the Impact of Normalizing and Using Amharic Informal Opinionated Features in Sentiment Analysis

Examine the Impact of Normalizing and Using Amharic Informal Opinionated Features in Sentiment Analysis | 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 Examine the Impact of Normalizing and Using Amharic Informal Opinionated Features in Sentiment Analysis Abebaw Zewudu, Guta Tesema Tufa, Getachew Alemu, Anchit Bijalwan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7138610/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Social media users currently express their ideas, opinions, and feelings using informal vocabulary. The majority of social media users commonly speak informally, using slang, misspellings, grammar mistakes, and abbreviations. Nowadays, people express their opinions most of the time informally. We tackle the issue of Amharic sentiment analysis by using informal opinionated words in Amharic as a feature and preprocessing it using normalization. We also study the impact of using reduced minimum word frequency parameter in an automated feature extractor that incorporates word and character n-gram embedding. Compared to earlier work approaches, the study’s highest recall result was 91.67 %; an average recall improvement of 2.8 was gained. Amharic Sentiment analysis Informal CNN-Bi-LSTM Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7138610","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":545032671,"identity":"46380844-43fe-4704-a30f-32c7f78cc274","order_by":0,"name":"Abebaw Zewudu","email":"","orcid":"","institution":"Wolkite University","correspondingAuthor":false,"prefix":"","firstName":"Abebaw","middleName":"","lastName":"Zewudu","suffix":""},{"id":545032672,"identity":"9055434a-949a-4b07-9799-a331f99c8863","order_by":1,"name":"Guta Tesema Tufa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYJADxgdQhgEBhcxAnABhGUBVGxDQhtDCJkGUFvmI/IMfGH/Y2POLHX5W8ePPn8QG9uZtEgwVf3BqMbyRzCzBkJCWOHN2mtnN3jaDxAaeY2USDGdw22I4I5kBqOVwgsHtBLMbvA1ALRI5ZhKMbXi1MP9gSPhvb387/Vvhnz9ALfJvgFr+4fGLRDLQ1wkHGDdI55gx87CBbOEBamnArcWA57GZRUJacuKM2znF0rJtxsZtPGnFFgnHjHHb0p74+MYHGzt7/tnpGz+++SMn289+eOONDzVyuG05wACLFihgY0AXQbelAY/kKBgFo2AUjAIwAAC/TE3N8p8hhgAAAABJRU5ErkJggg==","orcid":"","institution":"Adama Science and Technology University","correspondingAuthor":true,"prefix":"","firstName":"Guta","middleName":"Tesema","lastName":"Tufa","suffix":""},{"id":545032673,"identity":"87b64f70-bc19-42f8-8b14-cd01c86b87ba","order_by":2,"name":"Getachew Alemu","email":"","orcid":"","institution":"Addis Ababa Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Getachew","middleName":"","lastName":"Alemu","suffix":""},{"id":545032674,"identity":"36c398c4-0fae-48f4-8e83-28994994bc08","order_by":3,"name":"Anchit Bijalwan","email":"","orcid":"","institution":"British University","correspondingAuthor":false,"prefix":"","firstName":"Anchit","middleName":"","lastName":"Bijalwan","suffix":""}],"badges":[],"createdAt":"2025-07-16 09:53:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7138610/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7138610/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96246815,"identity":"dac0fb6c-38e6-405c-8278-bf538ff275f6","added_by":"auto","created_at":"2025-11-19 07:26:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":664189,"visible":true,"origin":"","legend":"","description":"","filename":"ExaminetheImpactofNormalizingandUsingAmharicInformalOpinionatedFeaturesinSentimentAnalysis.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7138610/v1_covered_eeba313d-c779-4d92-9d70-db1cabf009f3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Examine the Impact of Normalizing and Using Amharic Informal Opinionated Features in Sentiment Analysis","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Amharic, Sentiment analysis, Informal, CNN-Bi-LSTM","lastPublishedDoi":"10.21203/rs.3.rs-7138610/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7138610/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSocial media users currently express their ideas, opinions, and feelings using informal vocabulary. The majority of social media users commonly speak informally, using slang, misspellings, grammar mistakes, and abbreviations. Nowadays, people express their opinions most of the time informally. We tackle the issue of Amharic sentiment analysis by using informal opinionated words in Amharic as a feature and preprocessing it using normalization. We also study the impact of using reduced minimum word frequency parameter in an automated feature extractor that incorporates word and character n-gram embedding. 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