Graph Communities to Analyze the Occupational Accidents: An Evidence from The Statistics of Turkey 2013–2014

Year 2017, Volume: 30 Issue: 4, 373 - 393, 11.12.2017

Gökhan Tuna , Mustafa Kurt

Abstract

In this
study, we present an efficient graph clustering method called graph communities
to analyze occupational accidents in Turkey from 2013 to 2014 and use the
Pearson correlation to calculate the similarity measure between the accident
data. For this purpose we represent each accident as a vector of a social
actor. Then, we obtain sub-communities which can be seen as the cluster of
clusters iteratively. Moreover, we present the sub-dominant ultra-metric
structures among occupational accidents using the minimum spanning tree method.
In each sub-community we analyze the central nodes in minimum spanning trees
which are the dominant in the information flow. Furthermore, we use the
topological measures to determine which hierarchical structure is best to
represent occupational accidents in sub-communities.

Keywords

Occupational Accidents, Network Analysis, Pearson Correlation, Graph Communities, Minimum Spanning Tree

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