{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T04:28:23Z","timestamp":1777696103138,"version":"3.51.4"},"reference-count":25,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IDA"],"published-print":{"date-parts":[[2022,1,13]]},"abstract":"<jats:p>Influence maximization (IM) is a problem of selecting k nodes from social networks to make the expected number of the active node maximum. Recently, with the popularity of Internet technology, more and more researchers have paid attention to this problem. However, the existing influence maximization algorithms with high accuracy are usually difficult to be applied to the large-scale social network. To solve this problem the paper proposes a new algorithm, called community-based influence maximization (ComIM). Its core idea is \u201cdivide and conquer\u201d. In detail, this algorithm first utilizes the Louvain algorithm to divide the large-scale networks into some small-scale networks. Afterwards, the algorithm utilizes the one-hop diffusion value (ODV) and two-hop diffusion value (TDV) functions to calculate the influence of a node and select nodes on these small-scale networks, which can improve the accuracy of our proposed algorithm. By using the above methods, the paper proposes a community influence-estimating method called CDV, which can improve the efficiency of the algorithm. Experimental results on six real-world datasets demonstrate that our proposed algorithm outperforms all comparison algorithms when comprehensively considering the accuracy and efficiency.<\/jats:p>","DOI":"10.3233\/ida-205566","type":"journal-article","created":{"date-parts":[[2022,1,18]],"date-time":"2022-01-18T14:48:53Z","timestamp":1642517333000},"page":"205-220","source":"Crossref","is-referenced-by-count":1,"title":["ComIM: A community-based algorithm for influence maximization under the weighted cascade model on social networks"],"prefix":"10.1177","volume":"26","author":[{"given":"Liqing","family":"Qiu","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, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongqi","family":"Yang","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, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiwei","family":"Zhu","sequence":"additional","affiliation":[{"name":"Qilu University of Technology\/Shandong Academy of Sciences, Jinan, Shandong, China"},{"name":"Information Research Institute of Shandong Academy of Sciences, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangbo","family":"Tian","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, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuqi","family":"Liu","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, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"3","key":"10.3233\/IDA-205566_ref1","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.jnca.2014.01.015","article-title":"Predicting the content dissemination trends by repost behavior modeling in mobile social networks","volume":"42","author":"Lu","year":"2014","journal-title":"Journal of Network and Computer Applications"},{"issue":"1","key":"10.3233\/IDA-205566_ref2","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/MNET.2016.7389831","article-title":"Big data in mobile social networks: A QoE-oriented framework","volume":"30","author":"Su","year":"2016","journal-title":"IEEE Network"},{"issue":"1\u20132","key":"10.3233\/IDA-205566_ref3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12243-017-0624-1","article-title":"Design of reliable communication networks","volume":"73","author":"Gourdin","year":"2018","journal-title":"Annals of Telecommunications"},{"key":"10.3233\/IDA-205566_ref4","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1016\/j.ins.2016.07.012","article-title":"Influence maximization in social networks based on discrete particle swarm optimization","volume":"367\u2013368","author":"Gong","year":"2016","journal-title":"Information Sciences"},{"key":"10.3233\/IDA-205566_ref5","doi-asserted-by":"crossref","unstructured":"Influence maximization in social networks under an independent cascade-based model, Physica A Statistical Mechanics & Its Applications 444 (2016), 20\u201334.","DOI":"10.1016\/j.physa.2015.10.020"},{"key":"10.3233\/IDA-205566_ref7","doi-asserted-by":"crossref","unstructured":"M. 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