{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:13:06Z","timestamp":1769904786955,"version":"3.49.0"},"reference-count":23,"publisher":"Emerald","issue":"7","license":[{"start":{"date-parts":[[2016,11,14]],"date-time":"2016-11-14T00:00:00Z","timestamp":1479081600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["OIR"],"published-print":{"date-parts":[[2016,11,14]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>With the development and application of mobile internet access, social media represented by Weibo, WeChat, etc. has become the main channel for information release and sharing. High-impact users in social networks are key factors stimulating the large-scale propagation of information within social networks. User influence is usually related to the user\u2019s attention rate, activity level, and message content. The paper aims to discuss these issues.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>In this paper, the authors focused on Sina Weibo users, centered on users\u2019 behavior and interactive information, and formulated a weighted interactive information network model, then present a novel computational model for Weibo user influence, which combined multiple indexes such as the user\u2019s attention rate, activity level, and message content influence, etc., the model incorporated the time dimension, through the calculation of users\u2019 attribute influence and interactive influence, to comprehensively measure the user influence of Sina Weibo users.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Compared with other models, the model reflected the dynamics and timeliness of the user influence in a more accurate way. Extensive experiments are conducted on the real-world data set, and the results validate the performance of the approach, and demonstrate the effectiveness of the dynamics and timeliness. Due to the similarity in platform architecture and user behavior between Sina Weibo and Twitter, the calculation model is also applicable to Twitter.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This paper presents a novel computational model for Weibo user influence, which combined multiple indexes such as the user\u2019s attention rate, activity level, and message content influence, etc.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/oir-12-2015-0391","type":"journal-article","created":{"date-parts":[[2016,11,4]],"date-time":"2016-11-04T04:19:01Z","timestamp":1478233141000},"page":"867-881","source":"Crossref","is-referenced-by-count":24,"title":["Computational modeling of Weibo user influence based on information interactive network"],"prefix":"10.1108","volume":"40","author":[{"given":"Dingguo","family":"Yu","sequence":"first","affiliation":[]},{"given":"Nan","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Xu","family":"Ran","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020121121203995800_ref001","first-page":"522","article-title":"On flow authority discovery in social networks","year":"2011"},{"key":"key2020121121203995800_ref002","article-title":"Trends in social media: persistence and decay","year":"2011"},{"key":"key2020121121203995800_ref003","first-page":"10","article-title":"Measuring user influence in Twitter: the million follower fallacy","year":"2010","journal-title":"Proceedings of the International Conference on Weblogs and Social Media, ICWSM"},{"issue":"4","key":"key2020121121203995800_ref005","first-page":"884","article-title":"DiffRank: a novel algorithm for information diffusion detection in social networks","volume":"37","year":"2014","journal-title":"Chinese Journal of Computers"},{"issue":"3","key":"key2020121121203995800_ref006","first-page":"215","article-title":"Centrality in social networks conceptual clarification","volume":"1","year":"2012","journal-title":"Social Networks"},{"key":"key2020121121203995800_ref007","first-page":"241","article-title":"Learning influence probabilities in social networks","year":"2010"},{"issue":"5","key":"key2020121121203995800_ref008","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1145\/324133.324140","article-title":"Authoritative sources in a hyperlinked environment","volume":"46","year":"1999","journal-title":"Journal of the ACM"},{"key":"key2020121121203995800_ref009","first-page":"1562","article-title":"Mining topic-level opinion influence in microblog","year":"2012"},{"issue":"6","key":"key2020121121203995800_ref010","first-page":"1","article-title":"Hot topic propagation model and opinion leader identifying model in microblog network","year":"2013","journal-title":"Abstract and Applied Analysis"},{"issue":"2","key":"key2020121121203995800_ref011","first-page":"40","article-title":"The structure and function of complex networks","volume":"45","year":"2003","journal-title":"SIAM Review"},{"issue":"1","key":"key2020121121203995800_ref012","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.socnet.2004.11.009","article-title":"A measure of betweenness centrality based on random walks","volume":"27","year":"2005","journal-title":"Social Networks"},{"key":"key2020121121203995800_ref023","first-page":"45","article-title":"Identifying topical authorities in microblogs","year":"2011"},{"key":"key2020121121203995800_ref013","doi-asserted-by":"crossref","unstructured":"Romero, D.M., Galuba, W., Asur, S. and Huberman, B.A. (2011), \u201cInfluence and passivity in social media\u201d, Machine Learning and Knowledge Discovery in Databases, Springer, Berlin and Heidelberg, pp. 18-33.","DOI":"10.1145\/1963192.1963250"},{"key":"key2020121121203995800_ref014","first-page":"971","article-title":"Identifying opinion leaders in the blogosphere","year":"2007"},{"key":"key2020121121203995800_ref015","first-page":"509","article-title":"Information transfer in social media","year":"2012"},{"key":"key2020121121203995800_ref017","first-page":"2083","article-title":"Who are active? 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(2010), \u201cAlgorithms of BBS opinion leader mining based on sentiment analysis\u201d, Proceedings of the International Conference on Web Information Systems and Mining, Springer Berlin Heidelberg, pp. 360-369.","DOI":"10.1007\/978-3-642-16515-3_45"},{"key":"key2020121121203995800_ref004","unstructured":"Zhaoyun, D., Yan, J., Bin, Z., Jianfeng, Z., Yi, H. and Chunfeng, Y. (2013), \u201cAn influence strength measurement via time-aware probabilistic generative model for microblogs\u201d, Proceedings of the 15th Asia-Pacific Web Conference, APWeb, Springer Berlin Heidelberg, pp. 372-383."}],"container-title":["Online Information Review"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/OIR-12-2015-0391","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/OIR-12-2015-0391\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/OIR-12-2015-0391\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:44:23Z","timestamp":1753397063000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/oir\/article\/40\/7\/867-881\/454079"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,14]]},"references-count":23,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2016,11,14]]}},"alternative-id":["10.1108\/OIR-12-2015-0391"],"URL":"https:\/\/doi.org\/10.1108\/oir-12-2015-0391","relation":{},"ISSN":["1468-4527"],"issn-type":[{"value":"1468-4527","type":"print"}],"subject":[],"published":{"date-parts":[[2016,11,14]]}}}