Mapping Cultural Emotions in Smart Tourism Destinations: A Multimodal UGC Analysis and Affective Visualisation Framework Applied to Zhangjiajie, China

Mapping Cultural Emotions in Smart Tourism Destinations: A Multimodal UGC Analysis and Affective Visualisation Framework Applied to Zhangjiajie, China | 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 Article Mapping Cultural Emotions in Smart Tourism Destinations: A Multimodal UGC Analysis and Affective Visualisation Framework Applied to Zhangjiajie, China Ya Yu, Qingjun Xu, Yushen Wang, Maowei Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9332716/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Smart tourism increasingly emphasises emotional engagement in cultural communication, yet existing mapping systems predominantly rely on static displays that fail to capture visitors' authentic cultural sentiments. This study proposes a three-tiered "semantic–emotional–narrative" cultural sentiment visualisation framework, applied to Zhangjiajie, China. Analysing 18,667 UGC review texts, 2,043 images, and 128 official texts from Chinese tourism platforms (September 2020–September 2025), the framework integrates: (1) TF-IDF/TextRank semantic network analysis to extract cultural keyword clusters; (2) dual-channel sentiment analysis combining BERT-based aspect-level text modelling with facial emotion recognition (ResNet-50/AffectNet) and scene sentiment extraction (InceptionV3); and (3) spatial emotion mapping using kernel density estimation and LISA spatial autocorrelation in QGIS/GeoDa. Results reveal three cultural semantic clusters—peak forest landscapes, ecological nature, and ethnic culture—with significant spatial emotional autocorrelation (Global Moran's I = 0.437, p < 0.001). The multimodal fusion model (BiLSTM + InceptionV3) achieved F1 = 0.90 across 24 theme–emotion classes. An interactive cultural map prototype using Unity3D-GIS demonstrated emotion-driven narrative path generation, with three thematic routes exhibiting distinct emotional profiles. These findings contribute to integrating affective geography with smart tourism while providing a replicable pipeline for emotion-intelligent cultural communication design. Humanities/Cultural and media studies Social science/Cultural and media studies Scientific community and society/Geography Social science/Geography aspect-based sentiment analysis spatial emotion mapping multimodal user-generated content (UGC) affective geography heritage tourism narrative cartography Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 07 May, 2026 Editor assigned by journal 07 May, 2026 Editor invited by journal 22 Apr, 2026 Submission checks completed at journal 16 Apr, 2026 First submitted to journal 15 Apr, 2026 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-9332716","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":641515541,"identity":"573f93a6-97db-43d3-a8aa-fce3329b02c0","order_by":0,"name":"Ya Yu","email":"","orcid":"","institution":"Baotou Teachers College","correspondingAuthor":false,"prefix":"","firstName":"Ya","middleName":"","lastName":"Yu","suffix":""},{"id":641515542,"identity":"8d4fa041-ba48-40f7-8b21-0a78cfd27f19","order_by":1,"name":"Qingjun Xu","email":"","orcid":"","institution":"Baotou Teachers College","correspondingAuthor":false,"prefix":"","firstName":"Qingjun","middleName":"","lastName":"Xu","suffix":""},{"id":641515546,"identity":"1ff16a6c-9725-46d2-bb8c-5de84f175044","order_by":2,"name":"Yushen Wang","email":"","orcid":"","institution":"Kangwon National University","correspondingAuthor":false,"prefix":"","firstName":"Yushen","middleName":"","lastName":"Wang","suffix":""},{"id":641515547,"identity":"dda64cbb-9197-4ba8-a4f3-c18e96a26a6e","order_by":3,"name":"Maowei Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYJCCAx8OIPEkiNFycAbJWph5SNKiOyPH8LDNGbs8+YjkYw8YauwYJGcfwK/F7EaOweGcG8nFhjfS0g0YjiUzSPMlENKSu+FwzgfmxI2zc8wkGNgOMMjxEHAYWIvFh3qoln/EamG4cThxvjRQC2PbAQZpglrOvP9wsOfM8cQN8s/SJBL7knkkewhpOZ6W/OHHserE+T2Hj0l8+GYnJ3GGgBY4MDgAJBIYGAg5CwnINxCvdhSMglEwCkYYAABJxkZQAdEqDQAAAABJRU5ErkJggg==","orcid":"","institution":"Kangwon National University","correspondingAuthor":true,"prefix":"","firstName":"Maowei","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2026-04-06 10:23:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9332716/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9332716/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109799428,"identity":"0d6868dd-6ab7-4fab-ad8b-292eca53de44","added_by":"auto","created_at":"2026-05-22 15:28:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1388891,"visible":true,"origin":"","legend":"","description":"","filename":"revised2Manuscriptscientificreport.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9332716/v1_covered_1abd3544-7363-4e2e-b6fe-ad0346e0a3f2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mapping Cultural Emotions in Smart Tourism Destinations: A Multimodal UGC Analysis and Affective Visualisation Framework Applied to Zhangjiajie, China","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"aspect-based sentiment analysis, spatial emotion mapping, multimodal user-generated content (UGC), affective geography, heritage tourism, narrative cartography","lastPublishedDoi":"10.21203/rs.3.rs-9332716/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9332716/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSmart tourism increasingly emphasises emotional engagement in cultural communication, yet existing mapping systems predominantly rely on static displays that fail to capture visitors' authentic cultural sentiments. This study proposes a three-tiered \"semantic\u0026ndash;emotional\u0026ndash;narrative\" cultural sentiment visualisation framework, applied to Zhangjiajie, China. Analysing 18,667 UGC review texts, 2,043 images, and 128 official texts from Chinese tourism platforms (September 2020\u0026ndash;September 2025), the framework integrates: (1) TF-IDF/TextRank semantic network analysis to extract cultural keyword clusters; (2) dual-channel sentiment analysis combining BERT-based aspect-level text modelling with facial emotion recognition (ResNet-50/AffectNet) and scene sentiment extraction (InceptionV3); and (3) spatial emotion mapping using kernel density estimation and LISA spatial autocorrelation in QGIS/GeoDa. Results reveal three cultural semantic clusters\u0026mdash;peak forest landscapes, ecological nature, and ethnic culture\u0026mdash;with significant spatial emotional autocorrelation (Global Moran's I\u0026thinsp;=\u0026thinsp;0.437, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). 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