完整後設資料紀錄
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dc.contributor.authorHuang, CYen_US
dc.contributor.authorSun, CTen_US
dc.contributor.authorLin, HCen_US
dc.date.accessioned2014-12-08T15:20:15Z-
dc.date.available2014-12-08T15:20:15Z-
dc.date.issued2005-10-01en_US
dc.identifier.issn1460-7425en_US
dc.identifier.urihttp://hdl.handle.net/11536/14388-
dc.description.abstractAs part of Watts and Strogatz's small-world model of complex networks, local information mechanisms such as landscape properties are used to approximate real-world conditions in social simulations. The authors investigated the influence of local information on social simulations based on the small-world network model, using a cellular automata variation with added shortcuts as a test platform for simulating the spread of an epidemic disease or cultural values/ideas. Results from experimental simulations show that the percentage of weak individuals should be considered significant local information, but vertex degree influences and the distribution patterns of weak individuals should not. When exploring contagion problems, the results encourage a future emphasis on setting and the proportions of specific values of local information related to infection strength or resistance, and a reduced emphasis on the detailed topological structure of small-world network models and the distribution patterns of specific values of local information.en_US
dc.language.isoen_USen_US
dc.subjectsmall-world network modelen_US
dc.subjectcontagion problemen_US
dc.subjectlocal informationen_US
dc.subjectepidemic simulationen_US
dc.titleInfluence of local information on social simulations in small-world network modelsen_US
dc.typeArticleen_US
dc.identifier.journalJASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATIONen_US
dc.citation.volume8en_US
dc.citation.issue4en_US
dc.citation.epageen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000235217900003-
dc.citation.woscount0-
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