{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T21:05:46Z","timestamp":1769634346109,"version":"3.49.0"},"reference-count":90,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T00:00:00Z","timestamp":1769558400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014440","name":"Ministry of Science, Innovation and Universities","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"crossref","award":["PID2024-155586OB-I00 (MCIU\/AEI\/10.13039\/501100011033)"],"award-info":[{"award-number":["PID2024-155586OB-I00 (MCIU\/AEI\/10.13039\/501100011033)"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100011941","name":"Government of the Principality of Asturias","doi-asserted-by":"crossref","award":["GRU-GIC-24-070"],"award-info":[{"award-number":["GRU-GIC-24-070"]}],"id":[{"id":"10.13039\/100011941","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>\n                    This research investigates the feasibility of inferring key demographic features, specifically gender and age, from analyzing the performance of fundamental interactive tasks by anonymous users of an e-commerce site. A dataset of interaction patterns from 592 volunteers, encompassing tasks such as\n                    <jats:italic>Point &amp; Click, Drag &amp; Drop, Text Selection, Text Editing<\/jats:italic>\n                    , and\n                    <jats:italic>Menu Item Selection<\/jats:italic>\n                    , was collected and analyzed. Various artificial intelligence (AI) models were trained to identify predictive correlations between task execution times and user demographics. Rigorous evaluation using metrics like Area Under the Curve of the Precision-Recall Curve (AUC-PR) demonstrated the models\u2019 efficacy in automatic user profiling, revealing the potential for highly accurate gender determination and age group estimation. These findings highlight the significant potential of AI to create systems for automatically inferring user demographics from initial interactions, enabling dynamic and personalized e-commerce experiences that enhance customer perception and potentially increase revenue.\n                  <\/jats:p>","DOI":"10.7717\/peerj-cs.3563","type":"journal-article","created":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T08:56:43Z","timestamp":1769590603000},"page":"e3563","source":"Crossref","is-referenced-by-count":0,"title":["AI models for demographic prediction in e-commerce: age and gender from initial user interactions"],"prefix":"10.7717","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6887-4087","authenticated-orcid":true,"given":"Javier","family":"De Andr\u00e9s","sequence":"first","affiliation":[{"name":"Deparment of Accounting, Universidad de Oviedo, Oviedo, Asturias, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5666-9809","authenticated-orcid":true,"given":"Daniel","family":"Fernandez-Lanvin","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad de Oviedo, Oviedo, Asturias, Spain"}]},{"given":"Martin","family":"Gonzalez-Rodriguez","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad de Oviedo, Oviedo, Asturias, Spain"}]},{"given":"Beatriz","family":"Pariente-Martinez","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad de Oviedo, Oviedo, Asturias, Spain"}]}],"member":"4443","published-online":{"date-parts":[[2026,1,28]]},"reference":[{"key":"10.7717\/peerj-cs.3563\/ref-1","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1109\/ICALT.2010.142","article-title":"Playing games on the screen: adapting mouse interaction at early 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