{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T01:36:52Z","timestamp":1770514612935,"version":"3.49.0"},"reference-count":62,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AJIM"],"published-print":{"date-parts":[[2021,10,13]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purposes of this paper are to (1) explore how personality traits pertaining to the dominance influence steadiness compliance model manifest themselves in terms of user interaction behavior on social media and (2) examine whether social interaction data on social media platforms can predict user personality.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Social interaction data was collected from 198 users of Sina Weibo, a popular social media platform in China. Their personality traits were also measured via questionnaire. Machine learning techniques were applied to predict the personality traits based on the social interaction data.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results demonstrated that the proposed classifiers had high prediction accuracy, indicating that our approach is reliable and can be used with social interaction data on social media platforms to predict user personality. \u201cReposting,\u201d \u201cbeing reposted,\u201d \u201ccommenting\u201d and \u201cbeing commented on\u201d were found to be the key interaction features that reflected Weibo users' personalities, whereas \u201cliking\u201d was not found to be a key feature.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>The findings of this study are expected to enrich personality prediction research based on social media data and to provide insights into the potential of employing social media data for the purpose of personality prediction in the context of the Weibo social media platform in China.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ajim-02-2021-0048","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T13:39:44Z","timestamp":1630417184000},"page":"839-864","source":"Crossref","is-referenced-by-count":17,"title":["Predicting user personality with social interactions in Weibo"],"prefix":"10.1108","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5090-4265","authenticated-orcid":false,"given":"Yuting","family":"Jiang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7489-4439","authenticated-orcid":false,"given":"Shengli","family":"Deng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7447-1222","authenticated-orcid":false,"given":"Hongxiu","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0228-8971","authenticated-orcid":false,"given":"Yong","family":"Liu","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2021,9,1]]},"reference":[{"issue":"2","key":"key2021101214090374200_ref150","first-page":"106","article-title":"Exploiting user interest similarity and social links for micro-blog forwarding in mobile opportunistic networks","volume":"11","year":"2014","journal-title":"Pervasive and Mobile Computing"},{"issue":"1","key":"key2021101214090374200_ref001","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.im.2015.08.001","article-title":"Do context and personality matter? 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