Social network analysis via multi-state reliability and conditional influence models
Kellie Schneider,
Chase Rainwater,
Ed Pohl,
Ivan Hernandez and
Jose Emmanuel Ramirez-Marquez
Reliability Engineering and System Safety, 2013, vol. 109, issue C, 99-109
Abstract:
This paper incorporates multi-state reliability measures into the assessment of a social network in which influence is treated as a multi-state commodity that flows through the network. The reliability of the network is defined as the probability that at least a certain level of influence reaches an intended target. We consider an individual's influence level as a function of the influence levels received from preceding actors in the network. We define several communication functions which describe the level of influence a particular actor will pass along to other actors within the network. Illustrative examples are presented, and the network reliability under the various communication influence levels is computed using exhaustive enumeration for a small example and Monte Carlo simulation for larger, more realistic sized examples.
Keywords: Social networks; Multi-state reliability; Conditional influence; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832012001512
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:109:y:2013:i:c:p:99-109
DOI: 10.1016/j.ress.2012.07.007
Access Statistics for this article
Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares
More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().