Discover knowledge of big data in social networks using machine learning

Discover knowledge of big data in social networks using machine learning | 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 Discover knowledge of big data in social networks using machine learning Mahdi Ajdani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3500226/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 Big data is the product of human collective intelligence, which has a high cost with the development of e-commerce in terms of complexity, semantics, distribution and processing in web-based computing, cloud computing and computing intelligence. Big data is important only when it becomes useful knowledge and information. In this study, using the technique of text mining and content analysis, the economic phenomena of 1998 in the social network LinkedIn are studied and examined and all published posts are included. ; 2800 posts in four groups; Inflation and increase in the cost of living and increase in the price of goods, increase in wages of labors and employees, increase in the unemployment rate, change in the exchange rate of classification and correlation between categories are described by the characteristics of users. User posts were analyzed using Rapidminer software and text mining algorithms, and in the end, we concluded that the number of users who have been involved in inflation and rising living costs and rising commodity prices, the highest number of users. And people who have been following the exchange rate change have had the most contacts. Big Data Knowledge Discovery Social Networking Machine Learning 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-3500226","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":247818697,"identity":"213b56db-d826-43e2-bab0-1830b6ad1af7","order_by":0,"name":"Mahdi Ajdani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBAC+wYIzcPYkMDAkFBhx8DAzNyAV4sBmExgkINoOZMM1MJInBZjEMHA2HYAyCOkRSL34OPKHwyJze3Jzx48nHcgmr8dqOVHxTbcfuE5l2x4JoEhsbHnmblB4rYDuTMOMzYw9py5jdsW9h4zyQaQlhkJZhKJ247nNgC1MDO24dHCzGP+E6ilvnFG+jeJxDmHc+cT1AK0hRFiSw7QlobDuRsIagH6RbIhTQLolzdlEgnHknM3ArUcxOcX+xm5Bz822NgkbmxP3yb5o8Yud975wwcf/KjArQUY7yBCgsGwAUnsAB71MC0MDPL4VY2CUTAKRsFIBgABOV3NWSIfIgAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Mahdi","middleName":"","lastName":"Ajdani","suffix":""}],"badges":[],"createdAt":"2023-10-27 18:14:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3500226/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3500226/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72344514,"identity":"9a56b686-7c8b-4651-8793-4fb586e554ac","added_by":"auto","created_at":"2024-12-25 23:46:23","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":299345,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptJBD.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3500226/v1_covered_6672f6b8-ab1a-40e3-b612-3af40ad41191.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Discover knowledge of big data in social networks using machine learning","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Big Data, Knowledge Discovery, Social Networking, Machine Learning","lastPublishedDoi":"10.21203/rs.3.rs-3500226/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3500226/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBig data is the product of human collective intelligence, which has a high cost with the development of e-commerce in terms of complexity, semantics, distribution and processing in web-based computing, cloud computing and computing intelligence. 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