Identifying influential spreaders by gravity model considering multi-characteristics of nodes
How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an increasing attention and many influential spreaders identification methods have been proposed so far. A significant number of experiments indicate that depe...
Saved in:
| Published in | Scientific reports Vol. 12; no. 1; pp. 9879 - 11 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
14.06.2022
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an increasing attention and many influential spreaders identification methods have been proposed so far. A significant number of experiments indicate that depending on a single characteristic of nodes to reliably identify influential spreaders is inadequate. As a result, a series of methods integrating multi-characteristics of nodes have been proposed. In this paper, we propose a gravity model that effectively integrates multi-characteristics of nodes. The number of neighbors, the influence of neighbors, the location of nodes, and the path information between nodes are all taken into consideration in our model. Compared with well-known state-of-the-art methods, empirical analyses of the Susceptible-Infected-Recovered (SIR) spreading dynamics on ten real networks suggest that our model generally performs best. Furthermore, the empirical results suggest that even if our model only considers the second-order neighborhood of nodes, it still performs very competitively. |
|---|---|
| AbstractList | How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an increasing attention and many influential spreaders identification methods have been proposed so far. A significant number of experiments indicate that depending on a single characteristic of nodes to reliably identify influential spreaders is inadequate. As a result, a series of methods integrating multi-characteristics of nodes have been proposed. In this paper, we propose a gravity model that effectively integrates multi-characteristics of nodes. The number of neighbors, the influence of neighbors, the location of nodes, and the path information between nodes are all taken into consideration in our model. Compared with well-known state-of-the-art methods, empirical analyses of the Susceptible-Infected-Recovered (SIR) spreading dynamics on ten real networks suggest that our model generally performs best. Furthermore, the empirical results suggest that even if our model only considers the second-order neighborhood of nodes, it still performs very competitively. Abstract How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an increasing attention and many influential spreaders identification methods have been proposed so far. A significant number of experiments indicate that depending on a single characteristic of nodes to reliably identify influential spreaders is inadequate. As a result, a series of methods integrating multi-characteristics of nodes have been proposed. In this paper, we propose a gravity model that effectively integrates multi-characteristics of nodes. The number of neighbors, the influence of neighbors, the location of nodes, and the path information between nodes are all taken into consideration in our model. Compared with well-known state-of-the-art methods, empirical analyses of the Susceptible-Infected-Recovered (SIR) spreading dynamics on ten real networks suggest that our model generally performs best. Furthermore, the empirical results suggest that even if our model only considers the second-order neighborhood of nodes, it still performs very competitively. How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an increasing attention and many influential spreaders identification methods have been proposed so far. A significant number of experiments indicate that depending on a single characteristic of nodes to reliably identify influential spreaders is inadequate. As a result, a series of methods integrating multi-characteristics of nodes have been proposed. In this paper, we propose a gravity model that effectively integrates multi-characteristics of nodes. The number of neighbors, the influence of neighbors, the location of nodes, and the path information between nodes are all taken into consideration in our model. Compared with well-known state-of-the-art methods, empirical analyses of the Susceptible-Infected-Recovered (SIR) spreading dynamics on ten real networks suggest that our model generally performs best. Furthermore, the empirical results suggest that even if our model only considers the second-order neighborhood of nodes, it still performs very competitively.How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an increasing attention and many influential spreaders identification methods have been proposed so far. A significant number of experiments indicate that depending on a single characteristic of nodes to reliably identify influential spreaders is inadequate. As a result, a series of methods integrating multi-characteristics of nodes have been proposed. In this paper, we propose a gravity model that effectively integrates multi-characteristics of nodes. The number of neighbors, the influence of neighbors, the location of nodes, and the path information between nodes are all taken into consideration in our model. Compared with well-known state-of-the-art methods, empirical analyses of the Susceptible-Infected-Recovered (SIR) spreading dynamics on ten real networks suggest that our model generally performs best. Furthermore, the empirical results suggest that even if our model only considers the second-order neighborhood of nodes, it still performs very competitively. |
| ArticleNumber | 9879 |
| Author | Li, Zhe Huang, Xinyu |
| Author_xml | – sequence: 1 givenname: Zhe surname: Li fullname: Li, Zhe email: gislzneu@163.com organization: Software College, Shenyang University of Technology of China – sequence: 2 givenname: Xinyu surname: Huang fullname: Huang, Xinyu email: huangxinyu@mail.neu.edu.cn organization: Software College, Northeastern University of China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35701528$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9Uktv3CAYRFWqJk3zB3qoLPXSixueNlwqVVEfK0XKJTlWCPPYsMKwBTvS_vuw6zRNcggX4PtmhgHmPTiKKVoAPiL4FUHCzwtFTPAWYtwiCiFryRtwgiFlLSYYHz1ZH4OzUjawDoYFReIdOCash4hhfgL-rIyNk3c7H9eNjy7M-60KTdlmq4zNpRl2zTqrOz_tmjEZGxqdYvG1taeMc5h8q29VVnqqpTJ5XZrkmlih5QN461Qo9uxhPgU3P39cX_xuL69-rS6-X7aaUTi1PeOKWGzF4BC3yjmELcGd6ynHUPQEDmagolOOcOg4M5xTbSFSkJtOaT6QU7BadE1SG7nNflR5J5Py8lBIeS1Vrs6ClagToooghhynA3VqsE4YYup5TBOiq9a3RWs7D6M1ur5HVuGZ6PNO9Ldyne6kQKIXfV8FvjwI5PR3tmWSoy_ahqCiTXORuOs7gQnqaYV-fgHdpDnH-lQHFEVwQX166ujRyr9frAC8AHROpWTrHiEIyn1a5JIWWdMiD2mRpJL4C5L2k5p82t_Kh9epZKHWkNQQ2Pzf9iuse0OL1OA |
| CitedBy_id | crossref_primary_10_1038_s41598_022_27145_3 crossref_primary_10_1016_j_physa_2023_128941 crossref_primary_10_1088_1674_1056_ad20d6 crossref_primary_10_1016_j_jocs_2025_102540 crossref_primary_10_1038_s41598_024_59071_x crossref_primary_10_1038_s41598_024_55547_y crossref_primary_10_3390_e27030298 crossref_primary_10_1016_j_inffus_2023_102096 crossref_primary_10_1038_s41598_025_93387_6 crossref_primary_10_1007_s00521_024_10793_z crossref_primary_10_3390_app14020521 crossref_primary_10_1007_s11227_023_05296_y crossref_primary_10_1016_j_aej_2024_10_049 crossref_primary_10_1016_j_chaos_2024_115675 crossref_primary_10_1038_s41598_024_64122_4 crossref_primary_10_1007_s13278_024_01388_6 crossref_primary_10_1016_j_ress_2025_110900 crossref_primary_10_1016_j_physa_2024_130256 crossref_primary_10_1016_j_jocs_2024_102473 crossref_primary_10_1007_s12043_024_02864_6 crossref_primary_10_1016_j_idm_2023_10_003 crossref_primary_10_1038_s41598_023_43585_x crossref_primary_10_1016_j_chaos_2024_115501 crossref_primary_10_1109_JETCAS_2023_3283680 crossref_primary_10_1016_j_eswa_2023_119928 crossref_primary_10_1007_s11276_023_03496_1 crossref_primary_10_1016_j_knosys_2025_113023 crossref_primary_10_3390_buildings15020152 |
| Cites_doi | 10.1103/PhysRevLett.105.218701 10.1016/j.socnet.2007.04.002 10.1016/j.pharmthera.2013.01.016 10.1016/j.physa.2013.10.047 10.1016/j.eswa.2019.113092 10.1063/1.5055069 10.1103/PhysRevE.69.025103 10.1016/j.ins.2019.07.072 10.1023/A:1011129422190 10.1371/journal.pone.0251208 10.1142/S0219525903001067 10.1103/PhysRevE.85.026116 10.1038/ncomms10168 10.1103/PhysRevE.68.065103 10.1016/0378-8733(78)90021-7 10.1038/nphys1746 10.1016/j.knosys.2019.105464 10.1038/s41598-021-01218-1 10.1093/biomet/30.1-2.81 10.3390/e22040450 10.1080/0022250X.1972.9989806 10.1371/journal.pcbi.1001109 10.1088/1674-1056/ab77fe 10.1140/epjb/e2008-00370-y 10.1103/PhysRevE.74.036104 10.1016/j.knosys.2021.107198 10.1038/s41598-019-44930-9 10.1137/S0036144500371907 10.1109/TNET.2003.822655 10.1080/000368400421093 10.1038/srep05097 10.1073/pnas.200327197 10.1038/s41598-019-47119-2 10.1038/nrg2918 10.2307/3033543 10.1038/30918 10.1016/j.physa.2015.12.162 10.1016/j.ins.2021.01.053 10.1103/PhysRevLett.89.208701 10.1016/j.chaos.2020.110456 10.1016/j.physa.2008.01.113 10.1016/j.physrep.2016.06.007 10.1016/j.ecolmodel.2012.12.011 10.1038/s41598-021-84684-x 10.1145/1772690.1772756 10.1109/TCSII.2018.2877406 10.1145/1134271.1134277 |
| ContentType | Journal Article |
| Copyright | The Author(s) 2022 2022. The Author(s). The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: The Author(s) 2022 – notice: 2022. The Author(s). – notice: The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | C6C AAYXX CITATION NPM 3V. 7X7 7XB 88A 88E 88I 8FE 8FH 8FI 8FJ 8FK ABUWG AEUYN AFKRA AZQEC BBNVY BENPR BHPHI CCPQU DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M2P M7P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS Q9U 7X8 5PM DOA |
| DOI | 10.1038/s41598-022-14005-3 |
| DatabaseName | Springer Nature OA Free Journals CrossRef PubMed ProQuest Central (Corporate) Health & Medical Collection ProQuest Central (purchase pre-March 2016) Biology Database (Alumni Edition) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest SciTech Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland ProQuest Central Essentials Biological Science Collection ProQuest Central Natural Science Collection ProQuest One Community College ProQuest Central Korea Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Biological Sciences ProQuest Health & Medical Collection Medical Database Science Database Biological Science Database ProQuest Central Premium ProQuest One Academic Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic MEDLINE - Academic PubMed Central (Full Participant titles) Directory of Open Access Journals - May need to register for free articles |
| DatabaseTitle | CrossRef PubMed Publicly Available Content Database ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Central China ProQuest Biology Journals (Alumni Edition) ProQuest Central ProQuest One Applied & Life Sciences ProQuest One Sustainability ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | Publicly Available Content Database PubMed CrossRef MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: C6C name: Springer Nature OA Free Journals url: http://www.springeropen.com/ sourceTypes: Publisher – sequence: 2 dbid: DOA name: Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 3 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 4 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology |
| EISSN | 2045-2322 |
| EndPage | 11 |
| ExternalDocumentID | oai_doaj_org_article_16990f8151f84b4fabef9d3d3265c33c PMC9197977 35701528 10_1038_s41598_022_14005_3 |
| Genre | Journal Article |
| GroupedDBID | 0R~ 3V. 4.4 53G 5VS 7X7 88A 88E 88I 8FE 8FH 8FI 8FJ AAFWJ AAJSJ AAKDD ABDBF ABUWG ACGFS ACSMW ACUHS ADBBV ADRAZ AENEX AEUYN AFKRA AJTQC ALIPV ALMA_UNASSIGNED_HOLDINGS AOIJS AZQEC BAWUL BBNVY BCNDV BENPR BHPHI BPHCQ BVXVI C6C CCPQU DIK DWQXO EBD EBLON EBS ESX FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE KQ8 LK8 M0L M1P M2P M48 M7P M~E NAO OK1 PIMPY PQQKQ PROAC PSQYO RNT RNTTT RPM SNYQT UKHRP AASML AAYXX AFPKN CITATION PHGZM PHGZT NPM 7XB 8FK AARCD K9. PJZUB PKEHL PPXIY PQEST PQGLB PQUKI PRINS Q9U 7X8 5PM PUEGO |
| ID | FETCH-LOGICAL-c540t-758a3e2e9bf18eaff12e326f748209730bdb496af380f85d884ce01a08d6ac8b3 |
| IEDL.DBID | M48 |
| ISSN | 2045-2322 |
| IngestDate | Wed Aug 27 01:26:03 EDT 2025 Thu Aug 21 17:51:12 EDT 2025 Fri Jul 11 15:54:51 EDT 2025 Wed Aug 13 11:26:54 EDT 2025 Thu Apr 03 07:04:29 EDT 2025 Thu Apr 24 23:05:33 EDT 2025 Tue Jul 01 04:16:38 EDT 2025 Fri Feb 21 02:40:29 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| License | 2022. The Author(s). Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c540t-758a3e2e9bf18eaff12e326f748209730bdb496af380f85d884ce01a08d6ac8b3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | http://journals.scholarsportal.info/openUrl.xqy?doi=10.1038/s41598-022-14005-3 |
| PMID | 35701528 |
| PQID | 2676410174 |
| PQPubID | 2041939 |
| PageCount | 11 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_16990f8151f84b4fabef9d3d3265c33c pubmedcentral_primary_oai_pubmedcentral_nih_gov_9197977 proquest_miscellaneous_2676923174 proquest_journals_2676410174 pubmed_primary_35701528 crossref_primary_10_1038_s41598_022_14005_3 crossref_citationtrail_10_1038_s41598_022_14005_3 springer_journals_10_1038_s41598_022_14005_3 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2022-06-14 |
| PublicationDateYYYYMMDD | 2022-06-14 |
| PublicationDate_xml | – month: 06 year: 2022 text: 2022-06-14 day: 14 |
| PublicationDecade | 2020 |
| PublicationPlace | London |
| PublicationPlace_xml | – name: London – name: England |
| PublicationTitle | Scientific reports |
| PublicationTitleAbbrev | Sci Rep |
| PublicationTitleAlternate | Sci Rep |
| PublicationYear | 2022 |
| Publisher | Nature Publishing Group UK Nature Publishing Group Nature Portfolio |
| Publisher_xml | – name: Nature Publishing Group UK – name: Nature Publishing Group – name: Nature Portfolio |
| References | Wang, Li, Xia (CR19) 2018; 334 Bellingeri, Bevacqua, Scotognella, Cassi (CR51) 2019; 9 Xu, Li, Liang, Yu, Yang, Gao (CR4) 2019; 505 Ullah, Wang, Sheng, Long, Khan, Sun (CR24) 2021; 11 Csermely, Korcsmáros, Kiss, London, Nussinov (CR6) 2013; 138 Freeman (CR14) 1977; 40 CR35 Li, Ren, Ma, Liu, Zhang, Zhou (CR20) 2019; 9 Maji, Namtirtha, Dutta, Malta (CR29) 2020; 144 Watts, Strogatz (CR37) 1998; 393 Chen, Sun, Tang, Tian, Xie (CR47) 2019; 29 Karemera, Oguledo, Davis (CR16) 2000; 32 Lü, Chen, Ren, Zhang, Zhang, Zhou (CR9) 2016; 650 Lü, Zhou, Zhang, Stanley (CR11) 2016; 7 Newman (CR40) 2006; 74 CR2 Liu, Wang, Deng (CR21) 2020; 193 Castellano, Pastor-Satorras (CR32) 2010; 105 Wang, Yang, Liu, Ma (CR30) 2021; 16 Huang, Chen, Wang, Ren (CR28) 2020; 22 Kendall (CR33) 1938; 30 Li, Huang (CR27) 2021; 11 CR43 Hu, Wang (CR46) 2008; 387 CR41 Yan, Fu, Chen (CR49) 2008; 65 Yan, Cui, Ni (CR25) 2020; 29 Borge-Holthoefer, Moreno (CR3) 2012; 85 Newman (CR45) 2002; 89 Bonacich (CR13) 2007; 29 Amaral, Scala, Barthelemy, Stanley (CR48) 2000; 97 Bellingeri, Cassi, Vincenzi (CR8) 2013; 251 Hethcote (CR31) 2009; 42 Kitsak, Gallos, Havlin, Liljeros, Muchnik, Stanley (CR12) 2010; 6 Bonacich (CR10) 1972; 2 Mcauley, Leskovec (CR42) 2012; 25 Albert, Albert, Nakarado (CR5) 2004; 69 Gleiser, Danon (CR39) 2003; 6 Rocha, Liljeros, Holme (CR44) 2011; 7 Li, Shang, Deng (CR26) 2021; 143 Yang, Xiao (CR22) 2021; 227 Shang, Deng, Cheong (CR23) 2021; 577 Guimerà, Danon, Díaz-Guilera, Giralt, Arenas (CR36) 2003; 68 Bae, Kim (CR34) 2014; 395 Ma, Ma, Zhang, Wang (CR18) 2015; 451 Barabási, Gulbahce, Loscalzo (CR1) 2011; 12 Bellingeri, Bodini (CR7) 2016; 125 Porojan (CR17) 2001; 12 Spring, Mahajan, Wetherall, Anderson (CR38) 2004; 12 Wang, Tang, Yang, Do, Lai, Lee (CR50) 2014; 4 Freeman (CR15) 1979; 1 A Porojan (14005_CR17) 2001; 12 R Guimerà (14005_CR36) 2003; 68 X Wang (14005_CR30) 2021; 16 J Wang (14005_CR19) 2018; 334 HB Hu (14005_CR46) 2008; 387 LAN Amaral (14005_CR48) 2000; 97 J Borge-Holthoefer (14005_CR3) 2012; 85 LC Freeman (14005_CR14) 1977; 40 JJ Mcauley (14005_CR42) 2012; 25 14005_CR2 F Liu (14005_CR21) 2020; 193 N Spring (14005_CR38) 2004; 12 MEJ Newman (14005_CR40) 2006; 74 M Bellingeri (14005_CR8) 2013; 251 R Albert (14005_CR5) 2004; 69 Z Li (14005_CR20) 2019; 9 P Gleiser (14005_CR39) 2003; 6 X Yang (14005_CR22) 2021; 227 X Huang (14005_CR28) 2020; 22 LE Rocha (14005_CR44) 2011; 7 14005_CR43 14005_CR41 P Bonacich (14005_CR13) 2007; 29 HW Hethcote (14005_CR31) 2009; 42 DJ Watts (14005_CR37) 1998; 393 Q Shang (14005_CR23) 2021; 577 DB Chen (14005_CR47) 2019; 29 P Bonacich (14005_CR10) 1972; 2 G Yan (14005_CR49) 2008; 65 G Maji (14005_CR29) 2020; 144 LL Ma (14005_CR18) 2015; 451 MEJ Newman (14005_CR45) 2002; 89 M Kendall (14005_CR33) 1938; 30 A Ullah (14005_CR24) 2021; 11 L Lü (14005_CR11) 2016; 7 C Castellano (14005_CR32) 2010; 105 L Lü (14005_CR9) 2016; 650 D Karemera (14005_CR16) 2000; 32 X Yan (14005_CR25) 2020; 29 14005_CR35 M Bellingeri (14005_CR51) 2019; 9 M Bellingeri (14005_CR7) 2016; 125 H Li (14005_CR26) 2021; 143 M Kitsak (14005_CR12) 2010; 6 P Csermely (14005_CR6) 2013; 138 LC Freeman (14005_CR15) 1979; 1 AL Barabási (14005_CR1) 2011; 12 W Xu (14005_CR4) 2019; 505 W Wang (14005_CR50) 2014; 4 Z Li (14005_CR27) 2021; 11 J Bae (14005_CR34) 2014; 395 |
| References_xml | – volume: 105 start-page: 218701 year: 2010 ident: CR32 article-title: Thresholds for epidemic spreading in networks publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.105.218701 – volume: 29 start-page: 555 year: 2007 end-page: 564 ident: CR13 article-title: Some unique properties of eigenvector centrality publication-title: Soc. Netw. doi: 10.1016/j.socnet.2007.04.002 – volume: 138 start-page: 333 year: 2013 end-page: 408 ident: CR6 article-title: Structure and dynamics of molecular networks: A novel paradigm of drug discovery: a comprehensive review publication-title: Pharmacol. Ther. doi: 10.1016/j.pharmthera.2013.01.016 – volume: 395 start-page: 549 year: 2014 end-page: 559 ident: CR34 article-title: Identifying and ranking influential spreaders in complex networks by neighborhood coreness publication-title: Phys. A doi: 10.1016/j.physa.2013.10.047 – ident: CR35 – volume: 144 start-page: 113092 year: 2020 ident: CR29 article-title: Influential spreaders identification in complex networks with improved k-shell hybrid method publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.113092 – volume: 125 start-page: 586 year: 2016 end-page: 594 ident: CR7 article-title: Food web’s backbones and energy delivery in ecosystems publication-title: Sci. Rep. – volume: 29 start-page: 033120 year: 2019 ident: CR47 article-title: Identifying influential spreaders in complex networks by propagation probability dynamics publication-title: Chaos doi: 10.1063/1.5055069 – volume: 69 start-page: 025103 year: 2004 ident: CR5 article-title: Structural vulnerability of the North American power grid publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.69.025103 – volume: 505 start-page: 100 year: 2019 end-page: 126 ident: CR4 article-title: Identifying structural hole spanners to maximally block information propagation publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.07.072 – volume: 12 start-page: 265 year: 2001 end-page: 280 ident: CR17 article-title: Trade flows and spatial effects: The gravity model revisited publication-title: Open Econ. Rev. doi: 10.1023/A:1011129422190 – volume: 16 start-page: e0251208 year: 2021 ident: CR30 article-title: Comprehensive influence of topological location and neighbor information on identifying influential nodes in complex networks publication-title: PLoS ONE doi: 10.1371/journal.pone.0251208 – volume: 6 start-page: 565 year: 2003 ident: CR39 article-title: Community structure in Jazz publication-title: Adv. Complex Syst. doi: 10.1142/S0219525903001067 – volume: 85 year: 2012 ident: CR3 article-title: Absence of influential spreaders in rumor dynamics publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.85.026116 – volume: 7 start-page: 10168 year: 2016 ident: CR11 article-title: The H-index of a network node and its relation to degree and coreness publication-title: Nat. Commun. doi: 10.1038/ncomms10168 – volume: 68 start-page: 065103 year: 2003 ident: CR36 article-title: Self-similar community structure in a network of human interactions publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.68.065103 – volume: 334 start-page: 388 year: 2018 end-page: 400 ident: CR19 article-title: Improved centrality indicators to characterize the nodal spreading capability in complex networks publication-title: Appl. Math. Comput. – volume: 1 start-page: 215 year: 1979 end-page: 239 ident: CR15 article-title: Centrality in social networks conceptual clarification publication-title: Soc. Netw. doi: 10.1016/0378-8733(78)90021-7 – volume: 6 start-page: 888 year: 2010 end-page: 893 ident: CR12 article-title: Identification of influential spreaders in complex networks publication-title: Nat. Phys. doi: 10.1038/nphys1746 – volume: 193 start-page: 105464 year: 2020 ident: CR21 article-title: GMM: A generalized mechanics model for identifying the importance of nodes in complex networks publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2019.105464 – ident: CR43 – volume: 11 start-page: 22194 year: 2021 ident: CR27 article-title: Identifying influential spreaders in complex networks by an improved gravity model publication-title: Sci. Rep. doi: 10.1038/s41598-021-01218-1 – volume: 30 start-page: 81 year: 1938 end-page: 89 ident: CR33 article-title: A new measure of rank correlation publication-title: Biometrika doi: 10.1093/biomet/30.1-2.81 – ident: CR2 – volume: 22 start-page: 450 year: 2020 ident: CR28 article-title: Identifying influencers in social networks publication-title: Entropy doi: 10.3390/e22040450 – volume: 2 start-page: 113 year: 1972 end-page: 120 ident: CR10 article-title: Factoring and weighting approaches to status scores and clique identification publication-title: Math. Sociol. doi: 10.1080/0022250X.1972.9989806 – volume: 7 start-page: e1001109 year: 2011 ident: CR44 article-title: Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1001109 – volume: 29 start-page: 048902 year: 2020 ident: CR25 article-title: Identifying influential spreaders in complex networks based on entropy weight method and gravity law publication-title: Chinese Phys. B doi: 10.1088/1674-1056/ab77fe – volume: 65 start-page: 591 year: 2008 end-page: 594 ident: CR49 article-title: Epidemic threshold and phase transition in scale-free networks with asymmetric infection publication-title: Eur. Phys. J. B doi: 10.1140/epjb/e2008-00370-y – volume: 74 start-page: 036104 year: 2006 ident: CR40 article-title: Finding community structure in networks using the eigenvectors of matrices publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.74.036104 – volume: 227 start-page: 107198 year: 2021 ident: CR22 article-title: An improved gravity model to identify influential nodes in complex networks based on k-shell method publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2021.107198 – volume: 9 start-page: 8387 year: 2019 ident: CR20 article-title: Identifying influential spreaders by gravity model publication-title: Sci. Rep. doi: 10.1038/s41598-019-44930-9 – volume: 42 start-page: 599 year: 2009 end-page: 653 ident: CR31 article-title: The mathematics of infectious diseases publication-title: SIAM Rev. doi: 10.1137/S0036144500371907 – volume: 12 start-page: 2 year: 2004 end-page: 16 ident: CR38 article-title: Measuring ISP topologies with rocketfuel publication-title: IEEE/ACM Trans. Networking doi: 10.1109/TNET.2003.822655 – volume: 32 start-page: 1745 year: 2000 end-page: 1755 ident: CR16 article-title: A gravity model analysis of international migration to North America publication-title: Appl. Econ. doi: 10.1080/000368400421093 – volume: 4 start-page: 5097 year: 2014 ident: CR50 article-title: Asymmetrically interacting spreading dynamics on complex layered networks publication-title: Sci. Rep. doi: 10.1038/srep05097 – volume: 97 start-page: 11149 year: 2000 end-page: 11152 ident: CR48 article-title: Classes of small-world networks publication-title: PNAS doi: 10.1073/pnas.200327197 – volume: 9 start-page: 10692 year: 2019 ident: CR51 article-title: The heterogeneity in link weights may decrease the robustness of real-world complex weighted networks publication-title: Sci. Rep. doi: 10.1038/s41598-019-47119-2 – volume: 12 start-page: 56 year: 2011 end-page: 68 ident: CR1 article-title: Network medicine: A network-based approach to human disease publication-title: Nat. Rev. Genet. doi: 10.1038/nrg2918 – volume: 40 start-page: 35 year: 1977 end-page: 41 ident: CR14 article-title: A set of measures of centrality based on betweenness publication-title: Sociometry doi: 10.2307/3033543 – volume: 393 start-page: 440 year: 1998 end-page: 442 ident: CR37 article-title: Collective dynamics of ‘small-world’ networks publication-title: Nature doi: 10.1038/30918 – volume: 451 start-page: 205 year: 2015 end-page: 212 ident: CR18 article-title: Identifying influential spreaders in complex networks based on gravity formula publication-title: Phys. A doi: 10.1016/j.physa.2015.12.162 – volume: 577 start-page: 162 year: 2021 end-page: 179 ident: CR23 article-title: Identifying influential nodes in complex networks: Effective distance gravity model publication-title: Inform. Sciences doi: 10.1016/j.ins.2021.01.053 – volume: 25 start-page: 548 year: 2012 end-page: 556 ident: CR42 article-title: Learning to discover social circles in ego networks publication-title: Adv. Neural. Inf. Process. Syst. – volume: 89 start-page: 208701 year: 2002 ident: CR45 article-title: Assortative mixing in networks publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.89.208701 – volume: 143 start-page: 110456 year: 2021 ident: CR26 article-title: A generalized gravity model for influential spreaders identification in complex networks publication-title: Chaos Solitons Fract. doi: 10.1016/j.chaos.2020.110456 – volume: 387 start-page: 3769 year: 2008 end-page: 3780 ident: CR46 article-title: Unified index to quantifying heterogeneity of complex networks publication-title: Phys. A doi: 10.1016/j.physa.2008.01.113 – ident: CR41 – volume: 650 start-page: 1 year: 2016 end-page: 63 ident: CR9 article-title: Vital nodes identification in complex networks publication-title: Phys. Rep. doi: 10.1016/j.physrep.2016.06.007 – volume: 251 start-page: 1 year: 2013 end-page: 8 ident: CR8 article-title: Increasing the extinction risk of highly connected species causes a sharp robust-to-fragile transition in empirical food webs publication-title: Ecol. Model. doi: 10.1016/j.ecolmodel.2012.12.011 – volume: 11 start-page: 6173 year: 2021 ident: CR24 article-title: Identification of nodes influence based on global structure model in complex networks publication-title: Sci. Rep. doi: 10.1038/s41598-021-84684-x – volume: 227 start-page: 107198 year: 2021 ident: 14005_CR22 publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2021.107198 – volume: 6 start-page: 888 year: 2010 ident: 14005_CR12 publication-title: Nat. Phys. doi: 10.1038/nphys1746 – volume: 251 start-page: 1 year: 2013 ident: 14005_CR8 publication-title: Ecol. Model. doi: 10.1016/j.ecolmodel.2012.12.011 – volume: 29 start-page: 555 year: 2007 ident: 14005_CR13 publication-title: Soc. Netw. doi: 10.1016/j.socnet.2007.04.002 – volume: 42 start-page: 599 year: 2009 ident: 14005_CR31 publication-title: SIAM Rev. doi: 10.1137/S0036144500371907 – ident: 14005_CR43 doi: 10.1145/1772690.1772756 – volume: 505 start-page: 100 year: 2019 ident: 14005_CR4 publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.07.072 – volume: 16 start-page: e0251208 year: 2021 ident: 14005_CR30 publication-title: PLoS ONE doi: 10.1371/journal.pone.0251208 – volume: 25 start-page: 548 year: 2012 ident: 14005_CR42 publication-title: Adv. Neural. Inf. Process. Syst. – volume: 7 start-page: 10168 year: 2016 ident: 14005_CR11 publication-title: Nat. Commun. doi: 10.1038/ncomms10168 – volume: 577 start-page: 162 year: 2021 ident: 14005_CR23 publication-title: Inform. Sciences doi: 10.1016/j.ins.2021.01.053 – volume: 451 start-page: 205 year: 2015 ident: 14005_CR18 publication-title: Phys. A doi: 10.1016/j.physa.2015.12.162 – volume: 12 start-page: 2 year: 2004 ident: 14005_CR38 publication-title: IEEE/ACM Trans. Networking doi: 10.1109/TNET.2003.822655 – volume: 74 start-page: 036104 year: 2006 ident: 14005_CR40 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.74.036104 – volume: 334 start-page: 388 year: 2018 ident: 14005_CR19 publication-title: Appl. Math. Comput. – ident: 14005_CR2 doi: 10.1109/TCSII.2018.2877406 – volume: 29 start-page: 048902 year: 2020 ident: 14005_CR25 publication-title: Chinese Phys. B doi: 10.1088/1674-1056/ab77fe – volume: 12 start-page: 56 year: 2011 ident: 14005_CR1 publication-title: Nat. Rev. Genet. doi: 10.1038/nrg2918 – volume: 650 start-page: 1 year: 2016 ident: 14005_CR9 publication-title: Phys. Rep. doi: 10.1016/j.physrep.2016.06.007 – volume: 2 start-page: 113 year: 1972 ident: 14005_CR10 publication-title: Math. Sociol. doi: 10.1080/0022250X.1972.9989806 – volume: 9 start-page: 10692 year: 2019 ident: 14005_CR51 publication-title: Sci. Rep. doi: 10.1038/s41598-019-47119-2 – volume: 30 start-page: 81 year: 1938 ident: 14005_CR33 publication-title: Biometrika doi: 10.1093/biomet/30.1-2.81 – volume: 143 start-page: 110456 year: 2021 ident: 14005_CR26 publication-title: Chaos Solitons Fract. doi: 10.1016/j.chaos.2020.110456 – volume: 1 start-page: 215 year: 1979 ident: 14005_CR15 publication-title: Soc. Netw. doi: 10.1016/0378-8733(78)90021-7 – volume: 4 start-page: 5097 year: 2014 ident: 14005_CR50 publication-title: Sci. Rep. doi: 10.1038/srep05097 – volume: 97 start-page: 11149 year: 2000 ident: 14005_CR48 publication-title: PNAS doi: 10.1073/pnas.200327197 – volume: 32 start-page: 1745 year: 2000 ident: 14005_CR16 publication-title: Appl. Econ. doi: 10.1080/000368400421093 – volume: 138 start-page: 333 year: 2013 ident: 14005_CR6 publication-title: Pharmacol. Ther. doi: 10.1016/j.pharmthera.2013.01.016 – volume: 40 start-page: 35 year: 1977 ident: 14005_CR14 publication-title: Sociometry doi: 10.2307/3033543 – volume: 29 start-page: 033120 year: 2019 ident: 14005_CR47 publication-title: Chaos doi: 10.1063/1.5055069 – volume: 68 start-page: 065103 year: 2003 ident: 14005_CR36 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.68.065103 – volume: 11 start-page: 22194 year: 2021 ident: 14005_CR27 publication-title: Sci. Rep. doi: 10.1038/s41598-021-01218-1 – volume: 193 start-page: 105464 year: 2020 ident: 14005_CR21 publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2019.105464 – ident: 14005_CR35 – ident: 14005_CR41 doi: 10.1145/1134271.1134277 – volume: 144 start-page: 113092 year: 2020 ident: 14005_CR29 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.113092 – volume: 89 start-page: 208701 year: 2002 ident: 14005_CR45 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.89.208701 – volume: 22 start-page: 450 year: 2020 ident: 14005_CR28 publication-title: Entropy doi: 10.3390/e22040450 – volume: 393 start-page: 440 year: 1998 ident: 14005_CR37 publication-title: Nature doi: 10.1038/30918 – volume: 6 start-page: 565 year: 2003 ident: 14005_CR39 publication-title: Adv. Complex Syst. doi: 10.1142/S0219525903001067 – volume: 387 start-page: 3769 year: 2008 ident: 14005_CR46 publication-title: Phys. A doi: 10.1016/j.physa.2008.01.113 – volume: 395 start-page: 549 year: 2014 ident: 14005_CR34 publication-title: Phys. A doi: 10.1016/j.physa.2013.10.047 – volume: 7 start-page: e1001109 year: 2011 ident: 14005_CR44 publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1001109 – volume: 11 start-page: 6173 year: 2021 ident: 14005_CR24 publication-title: Sci. Rep. doi: 10.1038/s41598-021-84684-x – volume: 9 start-page: 8387 year: 2019 ident: 14005_CR20 publication-title: Sci. Rep. doi: 10.1038/s41598-019-44930-9 – volume: 125 start-page: 586 year: 2016 ident: 14005_CR7 publication-title: Sci. Rep. – volume: 85 year: 2012 ident: 14005_CR3 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.85.026116 – volume: 105 start-page: 218701 year: 2010 ident: 14005_CR32 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.105.218701 – volume: 69 start-page: 025103 year: 2004 ident: 14005_CR5 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.69.025103 – volume: 12 start-page: 265 year: 2001 ident: 14005_CR17 publication-title: Open Econ. Rev. doi: 10.1023/A:1011129422190 – volume: 65 start-page: 591 year: 2008 ident: 14005_CR49 publication-title: Eur. Phys. J. B doi: 10.1140/epjb/e2008-00370-y |
| SSID | ssj0000529419 |
| Score | 2.5618644 |
| Snippet | How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an increasing... Abstract How to identify influential spreaders in complex networks is a topic of general interest in the field of network science. Therefore, it wins an... |
| SourceID | doaj pubmedcentral proquest pubmed crossref springer |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 9879 |
| SubjectTerms | 639/766 639/766/530/2801 Decomposition Humanities and Social Sciences multidisciplinary Neighborhoods Nodes Science Science (multidisciplinary) |
| SummonAdditionalLinks | – databaseName: Directory of Open Access Journals - May need to register for free articles dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Li9swEB7KQqGXpe91mxYVemtNbEu2peNuaQiF9tRALouQbIkNBKdskkP-fWckx4237fbSqz2yxbzFaL4BeO-5R59nXeoxnFOZ0aSmcCZtUd4EY2izAKT99Vs1X4gvy3J5MuqL7oRFeODIuGleob_0EgMTftQKb6zzquUtph1lw3lD3hdj3slhKqJ6Fwp_3HfJZFxOtxipqJsMz154pqDy7ygSBcD-P2WZv1-WvFMxDYFo9hjO-wySXcadP4EHrnsKD-NMycMzuI6tt6F9ia3iCBK04jXD78Vry8weGE0dwvybhUE4rOmndtKScMMwbcY4zmzjWYek2-ewmH3-_mme9jMU0gZzsV2KxwHDXeGU9bl0xvu8cMg6XwsM_QrN27ZWqMp4LpHLZSulaFyWm0y2lWmk5S_grNt07gKYMlllLJde5U4IdJS2LMu2doJ6e2VWJZAf-ambHmCc5lysdSh0c6mjDDTKQAcZaJ7Ah2HNjwivcS_1FYlpoCRo7PAAFUb3CqP_pTAJTI5C1r29bnVR1ZUg7yQSeDe8Rkuj8onp3GYfaSgdJpqXUSeGnfCyxryqkAnUI20ZbXX8plvdBDRvlasak_AEPh716te2_s6KV_-DFa_hUUEGQaOYxATOdrd79wZzrJ19G8zpJ1BcIgM priority: 102 providerName: Directory of Open Access Journals – databaseName: Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1Bb9UwDLbG0CQuaMAYhTEFiRtUa5u0TU_ThpimSePEpHdBUZImMGlqx97bYf8eO8nrVGC7vrp9aW3HX-LYH8BHzz3OecblHsM5pRl1riun8x71TW0MTREaaZ9_a04vxNmiXqQNt2U6VrmeE8NE3Y-W9sgPqqZtBNmPOLz-nRNrFGVXE4XGE3hKrcvIqttFO-2xUBYL_z7VyhRcHiwxXlFNGa7AcGVBSeBZPApt-_-HNf89MvlX3jSEo5NteJ5wJDuKin8BG254CVuRWfLuFfyIBbihiIldRiIS9OUrhs-Lh5eZuWPEPYQonAU6HGYTdyfdEs4Z5nbezZmNng0outyBi5Ov37-c5olJIbeIyFY5Lgo0d5XrjC-l096XlUPc5luBAKBDJze9EV2jPZcFKq2XUlhXlLqQfaOtNPw1bA7j4N4A63TRaMOl70onBE6Xpq7rvnWCKnxl0WRQrr-nsqnNOLFdXKmQ7uZSRR0o1IEKOlA8g0_TPdexycaj0sekpkmSGmSHH8abnyr5myobDLNeIp5BWzTCa-N81_Me37q2nNsM9tZKVslrl-rexjL4MF1Gf6Mkih7ceBtlCBSTzG60iWkkvG4RXVUyg3ZmLbOhzq8Ml79CT--u7FqE4hl8XtvV_bAe_hRvH3-Ld_CsIlMnqiWxB5urm1v3HjHUyuwHR_kDsOMZVw priority: 102 providerName: ProQuest – databaseName: Springer Nature HAS Fully OA dbid: AAJSJ link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NT9wwEB1REFIvqHynBeRKvbURSewkznFBILQSXFokLsiyE5sioSxilwP_vjN2EhSgSFw3412vZ-x5zsy8AfjhuMMzz9jYoTunMKOOdWZ13KC-icbQJJ5I-_yiOLsU06v8agmyvhbGJ-17Skt_TPfZYYdzdDRUDIZXJ7wSUPT2E6wQVTva9spkMv09Hd6sUOwKf7SrkEm4fGPwyAt5sv63EObrRMkX0VLvhE6_wFqHHtkkzHcdlmy7Aauhn-TTJlyHsltfusRuQ_sR3MF3DL8vpCwz88So4xBib-ab4LC669hJQ3x2YVyPOZzZzLEWRedbcHl68uf4LO76J8Q14rBFjFcBzW1mK-NSabVzaWYRrblSoNuvcGubxoiq0I7LBFXVSClqm6Q6kU2ha2n4Niy3s9buAqt0UmjDpatSK3DRpcnzvCmtoLpemRQRpP16qrojF6ceF3fKB7m5VEEHCnWgvA4Uj-DnMOY-UGu8K31EahokiRbbfzB7uFGdmai0QOfqJKIYtEAjnDbWVQ1v8F_nNed1BHu9klW3V-cqK8pC0MkkIvg-PMZdRqET3drZY5AhKEwyO8EmhpnwvERMlckIypG1jKY6ftLe_vVM3lValQjAI_jV29XztP6_FF8_Jv4NPmdk-tRwSezB8uLh0e4jklqYg27r_AOGFBhy priority: 102 providerName: Springer Nature |
| Title | Identifying influential spreaders by gravity model considering multi-characteristics of nodes |
| URI | https://link.springer.com/article/10.1038/s41598-022-14005-3 https://www.ncbi.nlm.nih.gov/pubmed/35701528 https://www.proquest.com/docview/2676410174 https://www.proquest.com/docview/2676923174 https://pubmed.ncbi.nlm.nih.gov/PMC9197977 https://doaj.org/article/16990f8151f84b4fabef9d3d3265c33c |
| Volume | 12 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3db9MwED_tQ6C9IL4JjMpIvEEgiZ3EeUCoqzZNlTYhoFJfkGUnNkyqUmg7if733NlJodDxVCk5V67vzvdzz3c_gJeOO9zzjI0dhnNKM-pYZ1bHDeqb2hiaxDfSvrgszidiPM2ne9DTHXULuNx5tCM-qcli9ubnj_V7dPh3oWRcvl1iEKJCMTxW4XGBMrv7cIiRqSRGg4sO7ode31mF0-lqZ3YPPYLbPC8xSBI_-x-hynf03wVD_71N-VdK1Ueqs7twp4OYbBhs4h7s2fY-3Aqkk-sH8CXU5vr6JnYVOErQzWcMvy_ca2ZmzYiWCAE680w5rO5oPWmIv4IY19uNntncsRZFlw9hcnb6eXQedyQLcY1gbRXjeUFzm9nKuFRa7VyaWYR0rhSIDSr0f9MYURXacZmgPhspRW2TVCeyKXQtDX8EB-28tU-AVToptOHSVakVAndSk-d5U1pBxb8yKSJI-_VUddeBnIgwZspnwrlUQR0K1aG8OhSP4NVmzPfQf-O_0iekpo0k9c72D-aLr6pzRZUWGIGdRKiDZmqE08a6quEN_uq85ryO4LhXsurtUWVFWQjavkQELzav0RUpv6JbO78OMoSXSeZxsInNTHqbiqDcspatqW6_aa---XbfVVqViNIjeN3b1e9p3bwUT2-cwjM4ysjgiYBJHMPBanFtnyOyWpkB7JfTcgCHw-H40xg_T04vP3zEp6NiNPD_Vgy8Q_0CD4EiMQ |
| linkProvider | Scholars Portal |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwEB6VIgQXxJtAASPBCaImsZM4B4R4VVv6OLXSXpCxExsqVUnpboX2T_EbmbGTVOHRW6-JE9me8cxnj2c-gBeOO7R5xsYO3TmFGXWsM6vjBuVNZQxN4gtp7-0Xs0PxeZ7P1-DXkAtD1yoHm-gNddPVdEa-mRVlIUh_xNuTHzGxRlF0daDQCGqxY1c_ccu2eLP9EeX7Msu2Ph18mMU9q0BcIzpZxgiQNbeZrYxLpdXOpZlFDONKgc6wQoU3jRFVoR2XCQ6gkVLUNkl1IptC19Jw_O8VuIqON6HNXjkvxzMdiprhcPvcnITLzQX6R8phwx0f7mQo6Dzxf54m4F_Y9u8rmn_Eab3727oFN3vcyt4FRbsNa7a9A9cCk-XqLnwJCb8-aYodBeITtB3HDP8XLkszs2LEdYSon3n6HVb3XKH0ib_XGNfT6tGsc6zFpot7cHgpc3wf1tuutQ-BVToptOHSVakVAs2zyfO8Ka2gjGKZFBGkw3yqui9rTuwax8qH17lUQQYKZaC8DBSP4NX4zUko6nFh6_ckprElFeT2D7rTb6pf3yot0K07ifgJdd8Ip411VcMbHHVec15HsDEIWfVWYqHOdTqC5-NrXN8UtNGt7c5CGwLh1OZB0ImxJzwvEc1lMoJyoi2Trk7ftEfffQ3xKq1KhP4RvB706rxb_5-KRxeP4hlcnx3s7ard7f2dx3AjI7UnmiexAevL0zP7BPHb0jz1i4bB18tepb8B94dWbA |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwEB6VrUBcEG8CBYwEJ4g2iZ3EOSBEaVcthVWFqNQLMnZiQ6UqKd2t0P41fh0zzqMKj956TZzI9rw9nvkAnjvuUOcZGzo055Rm1KFOrA4rpDe1MTSRb6T9cZ7tHIj3h-nhGvzqa2HoWmWvE72irpqSzsinSZZngvhHTF13LWJ_a_bm5EdICFKUae3hNFoW2bOrnxi-LV7vbiGtXyTJbPvzu52wQxgIS_RUliE6y5rbxBbGxdJq5-LEoj_jcoGGsUDmN5URRaYdlxEuppJSlDaKdSSrTJfScPzvFVjPKSqawPrm9nz_03DCQzk0XHxXqRNxOV2gtaSKNoz_MK6hFPTIGnrQgH95un9f2Pwja-uN4ewm3Oi8WPa2ZbtbsGbr23C1xbVc3YEvbfmvL6FiRy0MCmqSY4b_a69OM7NihHyEMQDzYDys7JBD6RN_yzEsx72kWeNYjUMXd-HgUnb5HkzqprYPgBU6yrTh0hWxFQKVtUnTtMqtoPpiGWUBxP1-qrJrck5YG8fKJ9u5VC0NFNJAeRooHsDL4ZuTtsXHhaM3iUzDSGrP7R80p99UJ-0qztDIO4neFEqCEU4b64qKV7jqtOS8DGCjJ7LqdMZCnXN4AM-G1yjtlMLRtW3O2jHkktOY-y1PDDPhaY6-XSIDyEfcMprq-E199N13FC_iIsdAIIBXPV-dT-v_W_Hw4lU8hWsooerD7nzvEVxPiOsJ80lswGR5emYfozO3NE86qWHw9bIF9TfWzVwH |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Identifying+influential+spreaders+by+gravity+model+considering+multi-characteristics+of+nodes&rft.jtitle=Scientific+reports&rft.au=Li%2C+Zhe&rft.au=Huang%2C+Xinyu&rft.date=2022-06-14&rft.eissn=2045-2322&rft.volume=12&rft.issue=1&rft.spage=9879&rft_id=info:doi/10.1038%2Fs41598-022-14005-3&rft_id=info%3Apmid%2F35701528&rft.externalDocID=35701528 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2045-2322&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2045-2322&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2045-2322&client=summon |