{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:28:36Z","timestamp":1742912916628,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031211263"},{"type":"electronic","value":"9783031211270"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-21127-0_46","type":"book-chapter","created":{"date-parts":[[2023,1,3]],"date-time":"2023-01-03T19:38:43Z","timestamp":1672774723000},"page":"565-575","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Detecting Global Community Structure in\u00a0a\u00a0COVID-19 Activity Correlation Network"],"prefix":"10.1007","author":[{"given":"Hiroki","family":"Sayama","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,1,4]]},"reference":[{"issue":"5","key":"46_CR1","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1016\/S1473-3099(20)30120-1","volume":"20","author":"E Dong","year":"2020","unstructured":"Dong, E., Du, H., Gardner, L.: An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect. Dis. 20(5), 533\u2013534 (2020)","journal-title":"Lancet Infect. Dis."},{"unstructured":"Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. COVID-19 Data Repository. https:\/\/github.com\/CSSEGISandData\/COVID-19. Accessed on 5 June 2022","key":"46_CR2"},{"unstructured":"US Centers for Disease Control and Prevention (CDC). COVID Data Tracker. https:\/\/covid.cdc.gov\/covid-data-tracker\/. Accessed on 5 June 2022","key":"46_CR3"},{"unstructured":"World Health Organization. Coronavirus (COVID-19) Dashboard. https:\/\/covid19.who.int\/. Accessed on 5 June 2022","key":"46_CR4"},{"unstructured":"New York Times. Coronavirus World Map: Tracking the Global Outbreak. https:\/\/www.nytimes.com\/interactive\/2021\/world\/covid-cases.html. Accessed on 5 June 2022","key":"46_CR5"},{"unstructured":"Worldometer. COVID-19 Coronavirus Pandemic. https:\/\/www.worldometers.info\/coronavirus\/. Accessed on 5 June 2022","key":"46_CR6"},{"issue":"1","key":"46_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41597-020-0448-0","volume":"7","author":"B Xu","year":"2020","unstructured":"Xu, B., Gutierrez, B., Mekaru, S., et al.: Epidemiological data from the COVID-19 outbreak, real-time case information. Sci. Data 7(1), 1\u20136 (2020)","journal-title":"Sci. Data"},{"unstructured":"Global.health: A Data Science Initiative. https:\/\/global.health\/. Accessed on 5 June 2022","key":"46_CR8"},{"doi-asserted-by":"crossref","unstructured":"Cheng, C., Barcel\u00f3, J., Hartnett, A. S., Kubinec, R., Messerschmidt, L.: COVID-19 government response event dataset (CoronaNet v. 1.0). Nature Human Beh. 4(7), 756\u2013768 (2020)","key":"46_CR9","DOI":"10.1038\/s41562-020-0909-7"},{"doi-asserted-by":"crossref","unstructured":"Shuja, J., Alanazi, E., Alasmary, W., Alashaikh, A.: COVID-19 open source data sets: a comprehensive survey. Appl. Intel. 51(3), 1296\u20131325 (2021)","key":"46_CR10","DOI":"10.1007\/s10489-020-01862-6"},{"doi-asserted-by":"crossref","unstructured":"Binti Hamzah, F.A., Lau, C., Nazri, H., et al.: CoronaTracker: worldwide COVID-19 outbreak data analysis and prediction. Bulletin World Health Org. Preprint, 32 pages (2020)","key":"46_CR11","DOI":"10.2471\/BLT.20.255695"},{"unstructured":"CoronaTracker. https:\/\/www.coronatracker.com\/. Accessed on 5 June 2022","key":"46_CR12"},{"unstructured":"Mamoon, N., Rasskin, G.: COVID Visualizer. https:\/\/www.covidvisualizer.com\/. Accessed on 5 June 2022","key":"46_CR13"},{"unstructured":"Sayama, H.: COVID-19 Geographical Animation Generators. GitHub. https:\/\/github.com\/hsayama\/COVID-19-geographical-animations. Accessed on 5 June 2022","key":"46_CR14"},{"doi-asserted-by":"crossref","unstructured":"Sayama, H.: How artificial life researchers can help address complex societal challenges. In: ALIFE 2021: The 2021 Conference on Artificial Life, pp. 39\u201341. MIT Press (2021)","key":"46_CR15","DOI":"10.1162\/isal_a_00467"},{"issue":"14","key":"46_CR16","doi-asserted-by":"publisher","first-page":"3200","DOI":"10.1103\/PhysRevLett.86.3200","volume":"86","author":"R Pastor-Satorras","year":"2001","unstructured":"Pastor-Satorras, R., Vespignani, A.: Epidemic spreading in scale-free networks. Phys. Rev. Lett. 86(14), 3200 (2001)","journal-title":"Phys. Rev. Lett."},{"issue":"4","key":"46_CR17","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1140\/epjb\/e20020122","volume":"26","author":"Y Moreno","year":"2002","unstructured":"Moreno, Y., Pastor-Satorras, R., Vespignani, A.: Epidemic outbreaks in complex heterogeneous networks. Eur. Phys. J. B-Condensed Matter Complex Syst. 26(4), 521\u2013529 (2002)","journal-title":"Eur. Phys. J. B-Condensed Matter Complex Syst."},{"issue":"3","key":"46_CR18","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1103\/RevModPhys.87.925","volume":"87","author":"R Pastor-Satorras","year":"2015","unstructured":"Pastor-Satorras, R., Castellano, C., Van Mieghem, P., Vespignani, A.: Epidemic processes in complex networks. Rev. Modern Phys. 87(3), 925 (2015)","journal-title":"Rev. Modern Phys."},{"doi-asserted-by":"crossref","unstructured":"Masuda, N., Holme, P., eds.: Temporal Network Epidemiology. Springer (2017)","key":"46_CR19","DOI":"10.1007\/978-981-10-5287-3"},{"issue":"37","key":"46_CR20","doi-asserted-by":"publisher","first-page":"22684","DOI":"10.1073\/pnas.2010398117","volume":"117","author":"S Thurner","year":"2020","unstructured":"Thurner, S., Klimek, P., Hanel, R.: A network-based explanation of why most COVID-19 infection curves are linear. Proc. Nat. Acad. Sci. 117(37), 22684\u201322689 (2020)","journal-title":"Proc. Nat. Acad. Sci."},{"issue":"6164","key":"46_CR21","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1126\/science.1245200","volume":"342","author":"D Brockmann","year":"2013","unstructured":"Brockmann, D., Helbing, D.: The hidden geometry of complex, network-driven contagion phenomena. Science 342(6164), 1337\u20131342 (2013)","journal-title":"Science"},{"issue":"1","key":"46_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-021-04717-3","volume":"12","author":"D Tsiotas","year":"2022","unstructured":"Tsiotas, D., Tselios, V.: Understanding the uneven spread of COVID-19 in the context of the global interconnected economy. Sci. Rep. 12(1), 1\u201315 (2022)","journal-title":"Sci. Rep."},{"issue":"1","key":"46_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-020-18827-5","volume":"11","author":"F Della Rossa","year":"2020","unstructured":"Della Rossa, F., Salzano, D., Di Meglio, A., et al.: A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic. Nature Commun. 11(1), 1\u20139 (2020)","journal-title":"Nature Commun."},{"issue":"12","key":"46_CR24","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0261041","volume":"16","author":"E Amico","year":"2021","unstructured":"Amico, E., Bulai, I.M.: How political choices shaped Covid connectivity: the Italian case study. PLOS ONE 16(12), e0261041 (2021)","journal-title":"PLOS ONE"},{"key":"46_CR25","doi-asserted-by":"publisher","DOI":"10.3389\/fphy.2020.602075","volume":"8","author":"S Zhu","year":"2021","unstructured":"Zhu, S., Kou, M., Lai, F., Feng, Q., Du, G.: The connectedness of the coronavirus disease pandemic in the world: a study based on complex network analysis. Front. Phys. 8, 602075 (2021)","journal-title":"Front. Phys."},{"issue":"10","key":"46_CR26","doi-asserted-by":"publisher","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","volume":"2008","author":"VD Blondel","year":"2008","unstructured":"Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp. 2008(10), P10008 (2008)","journal-title":"J. Stat. Mech. Theory Exp."},{"unstructured":"Wolfram Language & System Documentation. FindGraphCommunities. https:\/\/reference.wolfram.com\/language\/ref\/FindGraphCommunities.html. Accessed on 5 June 2022","key":"46_CR27"}],"container-title":["Studies in Computational Intelligence","Complex Networks and Their Applications XI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21127-0_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,3]],"date-time":"2023-01-03T19:45:35Z","timestamp":1672775135000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21127-0_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031211263","9783031211270"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21127-0_46","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"type":"print","value":"1860-949X"},{"type":"electronic","value":"1860-9503"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"4 January 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"COMPLEX NETWORKS 2016","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Complex Networks and Their Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Palermo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwcna2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.complexnetworks.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}