Complex adaptive information flow and search transfer analysis

Szabolcs Feczak, Liaquat Hossain, Sven Carlsson

Research output: Contribution to journalArticle

Abstract

Studying information flow between node clusters can be conceptualised as an important challenge for the knowledge management research and practice community. We are confronted with issues related to establishing links between nodes and/or clusters during the process of information flow and search transfer in large distributed networks. In the case of missing socio-technical links, social networks can be instrumental in supporting the communities of practice interested in sharing and transferring knowledge across informal links. A comprehensive review of methodology for detecting missing links is provided. The proportion of common neighbours was selected as best practice to elicit missing links from a large health insurance data set. Weights were based on geographical arrangements of providers and the dollar value of transactions. The core network was elicited based on statistical thresholds. Suspicious, possibly fraudulent, behaviour is highlighted based on social network measures of the core. Our findings are supported by a health insurance industry expert panel.

Original languageEnglish
Pages (from-to)29-35
Number of pages7
JournalKnowledge Management Research and Practice
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Feb 2014
Externally publishedYes

Fingerprint Dive into the research topics of 'Complex adaptive information flow and search transfer analysis'. Together they form a unique fingerprint.

  • Cite this