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Physica D Nonlinear Phenomena
Article . 2006 . Peer-reviewed
License: Elsevier TDM
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zbMATH Open
Article . 2006
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Analysis of attachment models for directory and file trees

Authors: Klemm, Konstantin; Eguíluz, Víctor M.; Miguel, Maxi San;

Analysis of attachment models for directory and file trees

Abstract

Many networks emerge as the outcome of a collective interaction, like the WWW; others are the consequence of the biological evolution, like the brain. In contrast to these examples, we investigate the topology of trees generated by single individuals. Computer users generate directory structures to store and manage information in files. Analyzing the directory and file-trees generated by different users we have access to different realizations available for statistical analysis. We characterize the architecture of directories and files created by different computer users by means of the degree distributions and number of leaves, degree-degree correlations, average distance to the root, and community size distributions. We compare the different topologies in the search for similar managing patterns, and compare the trees obtained with two simple models of growing networks and with a model that interpolates between them and incorporates the heterogeneity of the computer users.

We acknowledge financial support from MCyT (Spain) through project CONOCE2, from Dutsche Forschungsgemeinschaft through Bioinformatics Initiative BIZ-6/1-2 and from Deutscher Akademischer Austauschdienst (DAAD).

7 pages, 6 figures.-- Printed version published Dec 2006.-- Issue title: "Dynamics on Complex Networks and Applications".

Full-text paper available Open Access at: http://ifisc.uib-csic.es/~victor/Filetrees/filetrees_PD.pdf

Keywords

Data structures, File trees, Graph theory (including graph drawing) in computer science, directory trees, Directory trees, Complex networks, complex networks, file trees

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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