[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125608-en":3,"doc-seo-125608-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125608,549758146520,"Patrick","https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470",8,"Research & Report","Luxury is what you say - Analyzing electronic word‐of‐mouth marketing of luxury products using artificial intelligence and machine learning","Many luxury brands invest heavily in dynamic video to actively engage consumers, yet evaluating performance from user comments is difficult because natural language is unstructured and comment volumes are large. Prior machine-learning and AI studies have not sufficiently addressed how brand type, perceived luxuriousness, and consumer diversity shape eWOM in luxury contexts. Using over 29,000 comments from 88 YouTube campaigns across nine luxury brands, the study applies automatic text and image analyses to test a conceptual framework. Findings show psycholinguistic differences by brand luxuriousness, Copelandian classification, and demographics, enabling more tailored dynamic content for diverse target segments.","City Research Online  \nCity St George’s, University of London  \nCitation: Oc, Y. , Plangger, K. , Sands, S. , Campbell, C. & Pitt, L. (2023) . Luxury is what you say: Analyzing electronic word‐of‐mouth marketing of luxury products using artificial intelligence and machine learning. Psychology and Marketing,  \n40(9), pp. 1704-1719. doi: 10.1002/mar.21831 This is the published version of the paper.  \nThis version of the publication may differ from the final published version. To cite this item please consult the publisher's version.  \nPermanent repository link: [https://openaccess.city.ac.uk/id/eprint/31016/](https://openaccess.city.ac.uk/id/eprint/31016/)  \nLink to published version: [https://doi.org/10.1002/mar.21831](https://doi.org/10.1002/mar.21831)  \nCopyright and Reuse: Copyright and Moral Rights remain with the author(s) and/or copyright holders. Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge, unless otherwise indicated, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. For full details of reuse please refer to City Research Online policy.  \nCity Research Online:  [http://openaccess.city.ac.uk/](http://openaccess.city.ac.uk/  publications@citystgeorges.ac.uk)[ ](http://openaccess.city.ac.uk/  publications@citystgeorges.ac.uk)[ publications@citystgeorges.ac.uk](http://openaccess.city.ac.uk/  publications@citystgeorges.ac.uk)  \nReceived: 23 September 2022  \nAccepted: 3  \nMay 2023  \nDOI: 10.1002/mar.21831  \nRES EARCH ARTICLE  \nLuxury is what you say: Analyzing electronic word‐of‐mouth marketing of luxury products using artificial intelligence and machine learning  \nYusuf Oc1  | Kirk Plangger1  | Sean Sands2  | Colin L. Campbell3 | Leyland Pitt4   \n1King's Business School, King's College London, London, UK  \n2Department of Management and Marketing, Swinburne University of Technology, Melbourne, Australia  \n3Knauss School of Business, University of San Diego, California, San Diego, USA  \n4Beedie School of Business, Simon Fraser University, Burnaby, Canada  \nCorrespondence  \nYusuf Oc, King's Business School, King's College London, 30 Aldwych, London WC2B 4BG, UK.  \nEmail: [yusuf.oc@kcl.ac.uk](yusuf.oc@kcl.ac.uk)  \nAbstract  \nMany luxury brands are investing heavily in creating dynamic video content to actively engage consumers. While it is straightforward to calculate the views or“likes” from a particular campaign to benchmark performance, analyzing consumers'comments on luxury brands' dynamic video content presents a challenge due to the unstructured nature of natural language and large comment volumes. Previous studies utilizing machine learning and artificial intelligence (AI) have not adequately examined the impact of brand types, brand luxuriousness, and consumer diversity. To address this research gap, this article tests a conceptual framework with over 29,000 comments from 88 YouTube campaigns for nine luxury brands using a combination of automatic text and image analyses. The results indicate significant differences in comments' psycholinguistic nature depending on the brand's luxuriousness (premium, prestige, and exquisite) and Copelandian classification (convenience, shopping, and specialty), as well as consumers' demographic characteristics (age, gender, and ethnicity) . These findings suggest that brand managers can use machine learning and AI methods to better tailor dynamic content creation to further engage diverse target segments by refining the campaign message to encourage additional engagement.  \nKEYWO R DS  \nautomatic text and image analysis, brand luxuriousness, luxury marketing communications, machine learning and artificial intelligence (AI), nature of electronic word‐of‐mouth (eWOM), social media video advertising, YouTube  \n1 | INTRODUCTION  \nWhile broadcast television remains a ","cbCaiqF9XaNVXlC6","https://ap.wps.com/l/cbCaiqF9XaNVXlC6","pdf",1156994,1,17,"English","en",105,"# Abstract\n## Research gap and objective\n## Data and methodology\n## Key findings and implications\n# Introduction\n## Social media video as an engagement channel\n## Need to study eWOM reactions","[{\"question\":\"Why is analyzing luxury brands' comments on video campaigns challenging?\",\"answer\":\"Comment analysis is difficult because natural language is unstructured and comment volumes are large, making traditional benchmarking limited to signals like views or likes.\"},{\"question\":\"What data and approach does the study use to analyze eWOM?\",\"answer\":\"The study analyzes over 29,000 comments from 88 YouTube campaigns for nine luxury brands using automatic text and image analyses.\"},{\"question\":\"What factors influence the psycholinguistic nature of consumers' comments?\",\"answer\":\"Results indicate differences depending on brand luxuriousness, Copelandian classification, and consumer demographics such as age, gender, and ethnicity.\"}]","Luxury is what you say - Analyzing electronic word‐of‐mouth marketing of luxury products using artificial intelligence and machine learning | PDF",1785900202,43,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"luxury-is-what-you-say-analyzing-electronic-wordofmouth-marketing-of-luxury-products-using-artificial-intelligence-and-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/luxury-is-what-you-say-analyzing-electronic-wordofmouth-marketing-of-luxury-products-using-artificial-intelligence-and-machine-learning/125608/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is analyzing luxury brands' comments on video campaigns challenging?","Question",{"text":75,"@type":76},"Comment analysis is difficult because natural language is unstructured and comment volumes are large, making traditional benchmarking limited to signals like views or likes.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What data and approach does the study use to analyze eWOM?",{"text":80,"@type":76},"The study analyzes over 29,000 comments from 88 YouTube campaigns for nine luxury brands using automatic text and image analyses.",{"name":82,"@type":73,"acceptedAnswer":83},"What factors influence the psycholinguistic nature of consumers' comments?",{"text":84,"@type":76},"Results indicate differences depending on brand luxuriousness, Copelandian classification, and consumer demographics such as age, gender, and ethnicity.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]