Publikationsdatum:
2010-05-15
Beschreibung:
Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities. We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices. This framework allows studies of community structure in a general setting encompassing networks that evolve over time, have multiple types of links (multiplexity), and have multiple scales.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Mucha, Peter J -- Richardson, Thomas -- Macon, Kevin -- Porter, Mason A -- Onnela, Jukka-Pekka -- New York, N.Y. -- Science. 2010 May 14;328(5980):876-8. doi: 10.1126/science.1184819.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, NC 27599, USA. mucha@unc.edu〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20466926" target="_blank"〉PubMed〈/a〉
Schlagwort(e):
*Algorithms
;
*Friends
;
*Group Processes
;
Humans
;
*Interpersonal Relations
;
*Models, Theoretical
;
Politics
;
*Population Groups
;
Time Factors
;
United States
Print ISSN:
0036-8075
Digitale ISSN:
1095-9203
Thema:
Biologie
,
Chemie und Pharmazie
,
Informatik
,
Medizin
,
Allgemeine Naturwissenschaft
,
Physik
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