{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T09:38:52Z","timestamp":1782380332076,"version":"3.54.5"},"reference-count":16,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2018,7,9]],"date-time":"2018-07-09T00:00:00Z","timestamp":1531094400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2018,7,27]]},"abstract":"<jats:p>Opinion leaders are those users who have great influence in social networks. It is significant to detect opinion leaders for the study on social networks and other applications. According to the key idea of the PageRank algorithm, a novel algorithm called HybridRank is proposed, taking into account topic-sensitive analysis and temporal characteristics. Our two major contributions are twofold: (1) topic-sensitive analysis is conducted to obtain the clusters in social networks; (2) temporal analysis is proposed to investigate the dynamics of the user\u2019s influence over the time. We also provide impressive experimental analysis on a real dataset grabbed from Chinese Sina BBS, showing that the proposed HybridRank Algorithm outperforms various related approaches.<\/jats:p>","DOI":"10.3233\/jifs-169607","type":"journal-article","created":{"date-parts":[[2018,7,10]],"date-time":"2018-07-10T14:31:29Z","timestamp":1531233089000},"page":"513-522","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Detecting opinion leaders in online social networks using HybridRank algorithm"],"prefix":"10.1177","volume":"35","author":[{"given":"Qiu","family":"Liqing","sequence":"first","affiliation":[{"name":"Shandong Province Key Laboratory of Wisdom Mine Information Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dai","family":"Jinlong","sequence":"additional","affiliation":[{"name":"Shandong Province Key Laboratory of Wisdom Mine Information Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liu","family":"Haiyan","sequence":"additional","affiliation":[{"name":"Shandong Province Key Laboratory of Wisdom Mine Information Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen","family":"Yan","sequence":"additional","affiliation":[{"name":"Shandong Province Key Laboratory of Wisdom Mine Information Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2018,7,9]]},"reference":[{"issue":"1","key":"e_1_3_2_2_2","first-page":"55","article-title":"Centrality and network flow G:\/Tex\/IOSPRESS\/IFS\/0-07\/IF01.eps","volume":"27","author":"Borgatti S.P.","year":"2005","unstructured":"BorgattiS.P., Centrality and network flow G:\/Tex\/IOSPRESS\/IFS\/0-07\/IF01.eps, SocialNetworks27 (1) (2005), 55\u201371.","journal-title":"SocialNetworks"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2012.06.047"},{"issue":"2","key":"e_1_3_2_4_2","first-page":"34","article-title":"Networking groups opinion leader identification algorithms based on sentiment analysis[J]","volume":"39","author":"Yu X.","year":"2012","unstructured":"YuX., Networking groups opinion leader identification algorithms based on sentiment analysis[J], Computer Science39 (2) (2012), 34\u201333.","journal-title":"Computer Science"},{"key":"e_1_3_2_5_2","first-page":"261","article-title":"TwitterRank: Finding topic-sensitive influential twitterers [J]","author":"Weng J.","year":"2010","unstructured":"WengJ., LimE.P., JiangJ., ., TwitterRank: Finding topic-sensitive influential twitterers [J], Wsdm (2010), 261\u2013270.","journal-title":"Wsdm"},{"key":"e_1_3_2_6_2","first-page":"187","article-title":"Content vs. context for sentiment analysis: A comparative analysisover microblogs[C]\/\/","author":"Aisopos F.","year":"2012","unstructured":"AisoposF., PapadakisG., TserpesK., ., Content vs. context for sentiment analysis: A comparative analysisover microblogs[C]\/\/, ACM Conference on Hypertext and Social Media ACM (2012), pp. 187\u2013196.","journal-title":"ACM Conference on Hypertext and Social Media ACM"},{"key":"e_1_3_2_7_2","first-page":"313","article-title":"Opinion mining over twitterspace: Classifying tweets programmatically using the R approach[C]\/\/","author":"Fiaidhi J.","year":"2012","unstructured":"FiaidhiJ., MohammedO., MohammedS., ., Opinion mining over twitterspace: Classifying tweets programmatically using the R approach[C]\/\/, Seventh International Conference on Digital Information Management IEEE (2012), pp. 313\u2013319.","journal-title":"Seventh International Conference on Digital Information Management IEEE"},{"key":"e_1_3_2_8_2","unstructured":"ZhangL. 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