{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T21:24:05Z","timestamp":1742937845514,"version":"3.40.3"},"publisher-location":"New York, NY","reference-count":36,"publisher":"Springer New York","isbn-type":[{"type":"print","value":"9781493971305"},{"type":"electronic","value":"9781493971312"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-1-4939-7131-2_180","type":"book-chapter","created":{"date-parts":[[2018,6,11]],"date-time":"2018-06-11T18:57:22Z","timestamp":1528743442000},"page":"1378-1392","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Models for Community Dynamics"],"prefix":"10.1007","author":[{"given":"Guandong","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haicheng","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,6,12]]},"reference":[{"key":"180_CR13388","doi-asserted-by":"publisher","first-page":"598","DOI":"10.1007\/3-540-45995-2_51","volume-title":"LATIN 2002: theoretical informatics","author":"J Abello","year":"2002","unstructured":"Abello J, Resende M, Sudarsky S (2002) Massive quasi-clique detection. In: LATIN 2002: theoretical informatics. Springer, Berlin, pp 598\u2013612"},{"key":"180_CR13389","doi-asserted-by":"crossref","unstructured":"Alvari H, Hajibagheri A, Sukthankar G (2014) Community detection in dynamic social networks: a game-theoretic approach. In: Advances in social networks analysis and mining (ASONAM), 2014 IEEE\/ACM international conference on IEEE, Beijing, pp 101\u2013107.","DOI":"10.1109\/ASONAM.2014.6921567"},{"issue":"4","key":"180_CR13390","doi-asserted-by":"publisher","first-page":"986","DOI":"10.1109\/TCYB.2015.2419263","volume":"46","author":"Z Bu","year":"2016","unstructured":"Bu Z, Wu Z, Cao J, Jiang Y (2016) Local community mining on distributed and dynamic networks from a multiagent perspective. IEEE Trans Cybern 46(4):986\u2013999","journal-title":"IEEE Trans Cybern"},{"issue":"2","key":"180_CR13391","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1007\/s10618-010-0186-6","volume":"21","author":"W Chen","year":"2010","unstructured":"Chen W, Liu Z, Sun X, Wang Y (2010) A game-theoretic framework to identify overlapping communities in social networks. Data Min Knowl Disc 21(2):224\u2013240","journal-title":"Data Min Knowl Disc"},{"key":"180_CR13392","doi-asserted-by":"crossref","unstructured":"Chi Y, Song X, Zhou D, Hino K, Tseng BL (2007) Evolutionary spectral clustering by incorporating temporal smoothness. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, San Jose, California, pp 153\u2013162","DOI":"10.1145\/1281192.1281212"},{"key":"180_CR13393","doi-asserted-by":"crossref","unstructured":"Feng W, Wang J (2012) Incorporating heterogeneous information for personalized tag recommendation in social tagging systems. In: Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, ACM, New York, NY, pp 1276\u20131284","DOI":"10.1145\/2339530.2339729"},{"issue":"3-5","key":"180_CR13394","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.physrep.2009.11.002","volume":"486","author":"Santo Fortunato","year":"2010","unstructured":"Fortunato S (2010) Community detection in graphs. Physics Reports. Elsevier, Amsterdam, 486, 75\u2013174","journal-title":"Physics Reports"},{"issue":"1","key":"180_CR13395","doi-asserted-by":"publisher","first-page":"012,805","DOI":"10.1103\/PhysRevE.92.012805","volume":"92","author":"C Granell","year":"2015","unstructured":"Granell C, Darst RK, Arenas A, Fortunato S, G\u00f3mez S (2015) Benchmark model to assess community structure in evolving networks. Phys Rev E 92(1):012,805","journal-title":"Phys Rev E"},{"issue":"2","key":"180_CR13396","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-985X.2007.00471.x","volume":"127","author":"MS Handcock","year":"2007","unstructured":"Handcock MS, Raftery AE, Tantrum JM (2007) Model-based clustering for social networks. J R Stat Soc Ser A 127(2):301\u2013354","journal-title":"J R Stat Soc Ser A"},{"key":"180_CR13397","doi-asserted-by":"crossref","unstructured":"Ji M, Han J, Danilevsky M (2011) Ranking-based classification of heterogeneous information networks. In: Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, San Diego, California, pp 1298\u20131306","DOI":"10.1145\/2020408.2020603"},{"issue":"10","key":"180_CR13398","doi-asserted-by":"publisher","first-page":"2743","DOI":"10.1109\/TPDS.2013.254","volume":"25","author":"Y Jiang","year":"2014","unstructured":"Jiang Y, Jiang J (2014) Understanding social networks from a multiagent perspective. IEEE Trans Parallel Distrib Syst 25(10):2743\u20132759","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"180_CR13399","doi-asserted-by":"publisher","first-page":"016,107","DOI":"10.1103\/PhysRevE.83.016107","volume":"83","author":"B Karrer","year":"2011","unstructured":"Karrer B, Newman MEJ (2011) Stochastic blockmodels and community structure in networks. Phys Rev E 83:016,107","journal-title":"Phys Rev E"},{"key":"180_CR13400","unstructured":"Kemp C, Tenenbaum JB, Griffiths TL, Yamada T, Ueda N (2006) Learning systems of concepts with an infinite relational model. In: Proceedings of the national conference on artificial intelligence, AAAI Press, Boston, Massachusetts. vol 21, p 381"},{"key":"180_CR13401","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1002\/j.1538-7305.1970.tb01770.x","volume":"49","author":"BW Kernighan","year":"1970","unstructured":"Kernighan BW, Lin S (1970) An efficient heuristic procedure for partitioning graphs. Bell Syst Tech J 49:291\u2013307","journal-title":"Bell Syst Tech J"},{"issue":"2","key":"180_CR13402","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1514888.1514891","volume":"3","author":"Yu-Ru Lin","year":"2009","unstructured":"Lin Y, Chi Y, Zhu S, Sundaram H, Tseng BL (2009) Analyzing communities and their evolutions in dynamic social networks. ACM Trans Knowl Discov Data 3(2.) Article 8","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"issue":"11","key":"180_CR13403","doi-asserted-by":"publisher","first-page":"2916","DOI":"10.1109\/TPDS.2014.2370031","volume":"26","author":"Z Lu","year":"2015","unstructured":"Lu Z, Sun X, Wen Y, Cao G, La Porta T (2015) Algorithms and applications for community detection in weighted networks. IEEE Trans Parallel Distrib Syst 26(11):2916\u20132926","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"180_CR13404","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/BF00139635","volume":"13","author":"R Mokken","year":"1979","unstructured":"Mokken R (1979) Cliques, clubs and clans. Qual Quant 13:161\u2013173","journal-title":"Qual Quant"},{"issue":"2","key":"180_CR13405","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1073\/pnas.98.2.404","volume":"98","author":"ME Newman","year":"2001","unstructured":"Newman ME (2001) The structure of scientific collaboration networks. Proc Natl Acad Sci 98(2):404\u2013409","journal-title":"Proc Natl Acad Sci"},{"issue":"2","key":"180_CR13406","doi-asserted-by":"publisher","first-page":"026,113","DOI":"10.1103\/PhysRevE.69.026113","volume":"69","author":"M Newman","year":"2004","unstructured":"Newman M, Girvan M (2004) Finding and evaulating community structrue in networks. Phys Rev E 69(2):026,113","journal-title":"Phys Rev E"},{"key":"180_CR13407","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1038\/nature03607","volume":"435","author":"G Palla","year":"2005","unstructured":"Palla G, Derenyi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 435:814\u2013818","journal-title":"Nature"},{"issue":"7136","key":"180_CR13408","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1038\/nature05670","volume":"446","author":"G Palla","year":"2007","unstructured":"Palla G, Barabasi AL, Vicsek T (2007) Quantifying social group evolution. Nature 446(7136):664\u2013667","journal-title":"Nature"},{"key":"180_CR13409","unstructured":"Scott J (2000) Social network analysis: a handbook. Sage, Los Angeles, California"},{"key":"180_CR13410","unstructured":"Slater PB (2008) Established clustering procedures for network analysis. Technical report. arXiv:0806.4168"},{"issue":"2","key":"180_CR13411","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00433ED1V01Y201207DMK005","volume":"3","author":"Y Sun","year":"2012","unstructured":"Sun Y, Han J (2012) Mining heterogeneous information networks: principles and methodologies. Synth Lect Data Min Knowl Disc 3(2):1\u2013159","journal-title":"Synth Lect Data Min Knowl Disc"},{"key":"180_CR13412","doi-asserted-by":"crossref","unstructured":"Sun Y, Yu Y, Han J (2009) Ranking-based clustering of heterogeneous information networks with star network schema. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, Paris, pp 797\u2013806","DOI":"10.1145\/1557019.1557107"},{"key":"180_CR13413","doi-asserted-by":"crossref","unstructured":"Sun Y, Norick B, Han J, Yan X, Yu PS, Yu X (2012) Interating meta-path selection with user-guided object clustering in heterogeneous information networks. In: Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining. Morgan & Claypool, San Rafael, California","DOI":"10.1145\/2339530.2339738"},{"issue":"1","key":"180_CR13414","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00298ED1V01Y201009DMK003","volume":"2","author":"Lei Tang","year":"2010","unstructured":"Tang L, Liu H (2010) Community detection and mining in social media. Morgan & Claypool, San Rafael, California","journal-title":"Synthesis Lectures on Data Mining and Knowledge Discovery"},{"issue":"1","key":"180_CR13415","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1109\/TKDE.2011.159","volume":"24","author":"L Tang","year":"2012","unstructured":"Tang L, Liu H, Zhang J (2012a) Identifying evolving groups in dynamic multimode networks. IEEE Trans Knowl Data Eng 24(1):72\u201385","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"180_CR13416","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10618-011-0231-0","volume":"25","author":"L Tang","year":"2012","unstructured":"Tang L, Wang X, Liu H (2012b) Community detection via heterogeneous interaction analysis. Data Min Knowl Disc 25:1\u201333","journal-title":"Data Min Knowl Disc"},{"key":"180_CR13417","doi-asserted-by":"crossref","unstructured":"Tantipathananandh C, Berger-Wolf T (2009) Constant-factor approximation algorithms for identifying dynamic communities. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, New York, NY, pp 827\u2013836","DOI":"10.1145\/1557019.1557110"},{"key":"180_CR13418","doi-asserted-by":"crossref","unstructured":"Tantipathananandh C, Berger-Wolf T, Kempe D (2007) A framework for community identification in dynamic social networks. In: Proceedings of 13th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, San Jose, California, pp 717\u2013726","DOI":"10.1145\/1281192.1281269"},{"key":"180_CR13419","doi-asserted-by":"crossref","unstructured":"Wu J, Xiong H, Chen J (2009) Adapting the right measures for k-means clustering. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, world text mining conference. pp 877\u2013886. ACM, New York, NY","DOI":"10.1145\/1557019.1557115"},{"key":"180_CR13420","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1007\/978-3-642-37210-0_22","volume-title":"Social Computing, Behavioral-Cultural Modeling and Prediction","author":"Kevin S. Xu","year":"2013","unstructured":"Xu KS, Hero III AO (2013) Dynamic stochastic blockmodels: statistical models for time-evolving networks. In: International conference on social computing, behavioral-cultural modeling, and prediction. Springer, pp 201\u2013210. Washington, DC"},{"issue":"2","key":"180_CR13421","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1109\/TKDE.2010.112","volume":"23","author":"Y Yang","year":"2011","unstructured":"Yang Y, Chen K (2011) Temporal data clustering via weighted clustering ensemble with different representations. IEEE Trans Knowl Data Eng 23(2):307\u2013320","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"180_CR13422","doi-asserted-by":"publisher","first-page":"990","DOI":"10.1137\/1.9781611972795.85","volume-title":"Proceedings of the 2009 SIAM International Conference on Data Mining","author":"Tianbao Yang","year":"2009","unstructured":"Yang T, Chi Y, Zhu S, Gao Y, Jin R (2009) A bayesian approach toward finding communities and their evolutions in dynamic social networks. In: Proceedings of the SAIM of the data mining. pp 990\u20131001. Society for Industrial and Applied Mathematics, Philadelphia, PA"},{"issue":"2","key":"180_CR13423","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/s10458-009-9080-2","volume":"20","author":"B Yang","year":"2010","unstructured":"Yang B, Liu J, Liu D (2010) An autonomy-oriented computing approach to community mining in distributed and dynamic networks. Auton Agent Multi-Agent Syst 20(2):123\u2013157","journal-title":"Auton Agent Multi-Agent Syst"}],"container-title":["Encyclopedia of Social Network Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-1-4939-7131-2_180","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T03:32:49Z","timestamp":1591155169000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-1-4939-7131-2_180"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9781493971305","9781493971312"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-1-4939-7131-2_180","relation":{},"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"12 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}