{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:41:34Z","timestamp":1762324894138,"version":"3.41.0"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030660451"},{"type":"electronic","value":"9783030660468"}],"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\/978-3-030-66046-8_36","type":"book-chapter","created":{"date-parts":[[2021,1,3]],"date-time":"2021-01-03T15:02:32Z","timestamp":1609686152000},"page":"437-450","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["MIDMod-OSN: A Microscopic-Level Information Diffusion Model for Online Social Networks"],"prefix":"10.1007","author":[{"given":"Abiola","family":"Osho","sequence":"first","affiliation":[]},{"given":"Colin","family":"Goodman","sequence":"additional","affiliation":[]},{"given":"George","family":"Amariucai","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,4]]},"reference":[{"issue":"3","key":"36_CR1","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1504\/IJWBC.2011.041206","volume":"7","author":"A Acar","year":"2011","unstructured":"Acar, A., Muraki, Y.: Twitter for crisis communication: lessons learned from japan\u2019s tsunami disaster. Int. J. Web Based Communities 7(3), 392\u2013402 (2011)","journal-title":"Int. J. Web Based Communities"},{"key":"36_CR2","doi-asserted-by":"crossref","unstructured":"Chen, W., Wang, C., Wang, Y.: Scalable influence maximization for prevalent viral marketing in large-scale social networks. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1029\u20131038. ACM (2010)","DOI":"10.1145\/1835804.1835934"},{"issue":"1","key":"36_CR3","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1109\/MIS.2005.16","volume":"20","author":"P Domingos","year":"2005","unstructured":"Domingos, P.: Mining social networks for viral marketing. IEEE Intell. Syst. 20(1), 80\u201382 (2005)","journal-title":"IEEE Intell. Syst."},{"key":"36_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1007\/978-3-319-47874-6_3","volume-title":"Social Informatics","author":"E Ferrara","year":"2016","unstructured":"Ferrara, E., Wang, W.-Q., Varol, O., Flammini, A., Galstyan, A.: Predicting online extremism, content adopters, and interaction reciprocity. In: Spiro, E., Ahn, Y.-Y. (eds.) SocInfo 2016. LNCS, vol. 10047, pp. 22\u201339. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-47874-6_3"},{"issue":"6","key":"36_CR5","doi-asserted-by":"publisher","first-page":"1420","DOI":"10.1086\/226707","volume":"83","author":"M Granovetter","year":"1978","unstructured":"Granovetter, M.: Threshold models of collective behavior. Am. J. Sociol. 83(6), 1420\u20131443 (1978)","journal-title":"Am. J. Sociol."},{"key":"36_CR6","doi-asserted-by":"crossref","unstructured":"Guille, A., Hacid, H., Favre, C.: Predicting the temporal dynamics of information diffusion in social networks. arXiv preprint arXiv:1302.5235 (2013)","DOI":"10.1145\/2503792.2503797"},{"key":"36_CR7","doi-asserted-by":"crossref","unstructured":"Kempe, D., Kleinberg, J., Tardos, \u00c9.: Maximizing the spread of influence through a social network. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 137\u2013146. ACM (2003)","DOI":"10.1145\/956750.956769"},{"issue":"1","key":"36_CR8","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1073\/pnas.1109739109","volume":"109","author":"K Lewis","year":"2012","unstructured":"Lewis, K., Gonzalez, M., Kaufman, J.: Social selection and peer influence in an online social network. Proc. Natl. Acad. Sci. 109(1), 68\u201372 (2012)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"36_CR9","unstructured":"Neppalli, V.K., Medeiros, M.C., Caragea, C., Caragea, D., Tapia, A.H., Halse, S.E.: Retweetability analysis and prediction during hurricane sandy. In: ISCRAM (2016)"},{"key":"36_CR10","doi-asserted-by":"crossref","unstructured":"Rao, A., Spasojevic, N., Li, Z., Dsouza, T.: Klout score: measuring influence across multiple social networks. In: 2015 IEEE International Conference on Big Data (Big Data), pp. 2282\u20132289. IEEE (2015)","DOI":"10.1109\/BigData.2015.7364017"},{"key":"36_CR11","unstructured":"Saito, K., Kimura, M., Ohara, K., Motoda, H.: Generative models of information diffusion with asynchronous timedelay. In: Proceedings of 2nd Asian Conference on Machine Learning, pp. 193\u2013208 (2010)"},{"key":"36_CR12","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/978-3-540-85567-5_9","volume-title":"Knowledge-Based Intelligent Information and Engineering Systems","author":"K Saito","year":"2008","unstructured":"Saito, K., Nakano, R., Kimura, M.: Prediction of information diffusion probabilities for independent cascade model. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds.) KES 2008. LNCS (LNAI), vol. 5179, pp. 67\u201375. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-85567-5_9"},{"key":"36_CR13","doi-asserted-by":"crossref","unstructured":"Spasojevic, N., Li, Z., Rao, A., Bhattacharyya, P.: When-to-post on social networks. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2127\u20132136. ACM (2015)","DOI":"10.1145\/2783258.2788584"},{"issue":"12","key":"36_CR14","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1145\/953460.953514","volume":"46","author":"MR Subramani","year":"2003","unstructured":"Subramani, M.R., Rajagopalan, B.: Knowledge-sharing and influence in online social networks via viral marketing. Commun. ACM 46(12), 300\u2013307 (2003)","journal-title":"Commun. ACM"},{"key":"36_CR15","doi-asserted-by":"crossref","unstructured":"Wang, F., Wang, H., Xu, K.: Diffusive logistic model towards predicting information diffusion in online social networks. In: 2012 32nd International Conference on Distributed Computing Systems Workshops (ICDCSW), pp. 133\u2013139. IEEE (2012)","DOI":"10.1109\/ICDCSW.2012.16"},{"key":"36_CR16","doi-asserted-by":"crossref","unstructured":"Xiang, R., Neville, J., Rogati, M.: Modeling relationship strength in online social networks. In: Proceedings of the 19th International Conference on World Wide Web, pp. 981\u2013990. ACM (2010)","DOI":"10.1145\/1772690.1772790"}],"container-title":["Lecture Notes in Computer Science","Computational Data and Social Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-66046-8_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T03:48:30Z","timestamp":1748836110000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-66046-8_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030660451","9783030660468"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-66046-8_36","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":"4 January 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CSoNet","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Data and Social Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dallas, TX","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","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":"11 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"csonet2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/optnetsci.cise.ufl.edu\/CSoNet\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"83","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3,4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}