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Birds of a feather scam together: Trustworthiness homophily in a business network
- Source :
- Social Networks. 54:228-237
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- Estimating the trustworthiness of a set of actors when all the available information is provided by the actors themselves is a hard problem. When two actors have conflicting reports about each other, how do we establish which of the two (if any) deserves our trust? In this paper, we model this scenario as a network problem: actors are nodes in a network and their reports about each other are the edges of the network. To estimate their trustworthiness levels, we develop an iterative framework which looks at all the reports about each connected actor pair to define its trustworthiness balance. We apply this framework to a customer/supplier business network. We show that our trustworthiness score is a significant predictor of the likelihood a business will pay a fine if audited. We show that the market network is characterized by homophily: businesses tend to connect to partners with similar trustworthiness degrees. This suggests that the topology of the network influences the behavior of the actors composing it, indicating that market regulatory efforts should take into account network theory to prevent further degeneration and failures.
- Subjects :
- Knowledge management
Sociology and Political Science
Computer science
business.industry
05 social sciences
General Social Sciences
02 engineering and technology
Audit
Network theory
Iterative framework
Homophily
Trustworthiness
020204 information systems
Anthropology
Business networking
0502 economics and business
0202 electrical engineering, electronic engineering, information engineering
050207 economics
Set (psychology)
business
General Psychology
Subjects
Details
- ISSN :
- 03788733
- Volume :
- 54
- Database :
- OpenAIRE
- Journal :
- Social Networks
- Accession number :
- edsair.doi...........55558f8d47f773da5c747710b50ea901
- Full Text :
- https://doi.org/10.1016/j.socnet.2018.01.009