{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T06:30:52Z","timestamp":1757313052041,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030630065"},{"type":"electronic","value":"9783030630072"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-63007-2_4","type":"book-chapter","created":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:02:39Z","timestamp":1606089759000},"page":"45-57","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Topic Diffusion Prediction on Bibliographic Network: New Approach with Combination Between External and Intrinsic Factors"],"prefix":"10.1007","author":[{"given":"Quang Vu","family":"Bui","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thi Kim Thoa","family":"Ho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marc","family":"Bui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,23]]},"reference":[{"key":"4_CR1","unstructured":"Akula, R., Yousefi, N., Garibay, I.: DeepFork: Supervised Prediction of Information Diffusion in GitHub, p. 12 (2019)"},{"key":"4_CR2","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. In: Dietterich, T.G., Becker, S., Ghahramani, Z. (eds.) Advances in Neural Information Processing Systems, vol. 14, pp. 601\u2013608. MIT Press, Cambridge (2002). http:\/\/papers.nips.cc\/paper\/2070-latent-dirichlet-allocation.pdf"},{"key":"4_CR3","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1007\/978-3-319-54472-4_24","volume-title":"Intelligent Information and Database Systems","author":"QV Bui","year":"2017","unstructured":"Bui, Q.V., Sayadi, K., Amor, S.B., Bui, M.: Combining latent dirichlet allocation and k-means for documents clustering: effect of probabilistic based distance measures. In: Nguyen, N.T., Tojo, S., Nguyen, L.M., Trawi\u0144ski, B. (eds.) ACIIDS 2017. LNCS (LNAI), vol. 10191, pp. 248\u2013257. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-54472-4_24"},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Goldenberg, J., Libai, B., Muller, E.: Talk of the network: a complex systems look at the underlying process of word-of-mouth. Mark. Lett. 12(3), 211\u2013223 (2001). https:\/\/doi.org\/10.1023\/A:1011122126881","DOI":"10.1023\/A:1011122126881"},{"key":"4_CR5","unstructured":"Granovetter, M.: Threshold models of collective behavior. Am. J. Sociol. 83(6), 1420\u20131443 (1978). https:\/\/www.journals.uchicago.edu\/doi\/abs\/10.1086\/226707"},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Gui, H., Sun, Y., Han, J., Brova, G.: Modeling topic diffusion in multi-relational bibliographic information networks. In: CIKM (2014)","DOI":"10.1145\/2661829.2662000"},{"key":"4_CR7","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1007\/978-3-319-98443-8_13","volume-title":"Computational Collective Intelligence","author":"TKT Ho","year":"2018","unstructured":"Ho, T.K.T., Bui, Q.V., Bui, M.: Homophily independent cascade diffusion model based on textual information. In: Nguyen, N.T., Pimenidis, E., Khan, Z., Trawi\u0144ski, B. (eds.) ICCCI 2018. LNCS (LNAI), vol. 11055, pp. 134\u2013145. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98443-8_13"},{"key":"4_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.1007\/11523468_91","volume-title":"Automata, Languages and Programming","author":"D Kempe","year":"2005","unstructured":"Kempe, D., Kleinberg, J., Tardos, \u00c9.: Influential nodes in a diffusion model for social networks. In: Caires, L., Italiano, G.F., Monteiro, L., Palamidessi, C., Yung, M. (eds.) ICALP 2005. LNCS, vol. 3580, pp. 1127\u20131138. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11523468_91"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Kempe, D., Kleinberg, J.M., Tardos, V.: Maximizing the spread of influence through a social network. In: KDD (2003)","DOI":"10.1145\/956750.956769"},{"key":"4_CR10","unstructured":"Macy, M.W.: Chains of cooperation: threshold effects in collective action. Am. Sociol. Rev. 56(6), 730\u2013747 (1991). https:\/\/www.jstor.org\/stable\/2096252"},{"key":"4_CR11","unstructured":"Molaei, S., Babaei, S., Salehi, M., Jalili, M.: Information spread and topic diffusion in heterogeneous information networks. Sci. Rep. 8(1), 1\u201314 (2018). https:\/\/www.nature.com\/articles\/s41598-018-27385-2"},{"key":"4_CR12","unstructured":"Molaei, S., Zare, H., Veisi, H.: Deep learning approach on information diffusion in heterogeneous networks. Knowl.-Based Syst., p. 105153 (2019). http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0950705119305076"},{"key":"4_CR13","unstructured":"Rosen-Zvi, M., Griffiths, T., Steyvers, M., Smyth, P.: The Author-Topic Model for Authors and Documents. arXiv:1207.4169 [cs, stat] (2012)"},{"key":"4_CR14","unstructured":"Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Inf. Process. Manag. 24(5), 513\u2013523 (1988). http:\/\/www.sciencedirect.com\/science\/article\/pii\/0306457388900210"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Sun, Y., Han, J., Yan, X., Yu, P.S., Wu, T.: Pathsim: meta path-based top-k similarity search in heterogeneous information networks. In: VLDB 11 (2011)","DOI":"10.14778\/3402707.3402736"},{"key":"4_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/978-3-319-09333-8_16","volume-title":"Intelligent Computing Theory","author":"D Varshney","year":"2014","unstructured":"Varshney, D., Kumar, S., Gupta, V.: Modeling information diffusion in social networks using latent topic information. In: Huang, D.-S., Bevilacqua, V., Premaratne, P. (eds.) ICIC 2014. LNCS, vol. 8588, pp. 137\u2013148. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-09333-8_16"},{"key":"4_CR17","unstructured":"Yang, H.: Mining social networks using heat diffusion processes for marketing candidates selection. ACM (2008). https:\/\/aran.library.nuigalway.ie\/handle\/10379\/4164"}],"container-title":["Lecture Notes in Computer Science","Computational Collective Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-63007-2_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:08:59Z","timestamp":1606090139000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-63007-2_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030630065","9783030630072"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-63007-2_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"23 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCCI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Collective Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Da Nang","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccci2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccci.pwr.edu.pl\/2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}