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Trust Transitivity in Social Networks

Overview of attention for article published in PLOS ONE, April 2011
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Title
Trust Transitivity in Social Networks
Published in
PLOS ONE, April 2011
DOI 10.1371/journal.pone.0018384
Pubmed ID
Authors

Oliver Richters, Tiago P. Peixoto

Abstract

Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust) is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected "fringe" nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its "fringe" peers.

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Mendeley readers

The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 3%
France 2 2%
Italy 2 2%
Hungary 1 <1%
Portugal 1 <1%
Ecuador 1 <1%
Netherlands 1 <1%
Slovenia 1 <1%
Denmark 1 <1%
Other 2 2%
Unknown 93 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 23%
Student > Master 23 21%
Researcher 13 12%
Professor > Associate Professor 8 7%
Student > Doctoral Student 8 7%
Other 21 19%
Unknown 10 9%
Readers by discipline Count As %
Computer Science 28 26%
Business, Management and Accounting 16 15%
Social Sciences 14 13%
Physics and Astronomy 6 6%
Engineering 5 5%
Other 22 20%
Unknown 17 16%