TEMPORAL SOCIAL NETWORK ANALYSIS FOR HISTORIANS - A Case Study

Abstract

Social network analysis has received much attention across disciplines. Recently, historians have begun to complicate their understanding of networks and are increasingly using visualisation to elucidate tangible and intangible information in their data sets. Current approaches make use of static social network analysis and whilst they provide a number of tools to explore a social network, they are unable to provide temporal analysis. This paper presents Matrixify, a practical visual application for the exploratory temporal analysis of social networks for historians and others not familiar with visual representations of data. This approach aims to deconstruct the complexity of social networks to provide a temporal analysis to answer a key problem in historical studies, that of 'analysis of change over time'. In this way, historians are able to identify real relationships in their data sets; actors in contact at a particular point in time and shown over time. The case study presented in this paper demonstrates the applicability of the approach in interdisciplinary studies.