![](bga.png)
Gildart). Therefore, were familial connections
deemed more trustworthy over non-familial, and
perhaps more influential, contacts? Were these
strategies successful? And was one more so than the
other?
Fifth, how does shifting actor engagement
impact on access to information, capital and the
ability to react to exogenous events? In this case,
how did the finance and networks of slave trade
networks change over time and did this affect their
strategy and ability to react to credit crises,
dislocation caused by war and abolition of the slave
trade?
These questions highlighted by the Matrixify
visualisation point to a need to conduct research in
further areas or themes and particular sources. This
is particularly important where there is a lack of
qualitative data about a network itself. In this case
the historian would want to conduct further research
on: the histories of the key families and their
networks (through secondary literature, family and
business papers); the changing responses to
exogenous conditions (through petitions to
Parliament, the records of similar associations in
London, House of Commons Sessional Papers and
Parliamentary Papers); the business networks of the
members (through business letters and accounts in
Liverpool, London and elsewhere); other
institutional membership (other clubs in Liverpool,
Town Council, etc.).
Matrixify therefore provides an exploratory tool
which highlights actor engagement and key trends in
a network. The questions raised by the historian
using such an analysis also point to avenues for
further research which may provide answers to these
questions. This is especially useful where qualitative
data is lacking for a particular network; a common
issue for historians.
6 CONCLUSIONS & FURTHER
WORK
Social network analysis has received much attention
across disciplines. The visualisation of networks
comprising both tangible and intangible information
has enabled researchers to understand how actors
use their relationships in their social lives. Recently,
historians have started to complicate their
understanding of networks in order to analyse their
data sets. This paper has presented Matrixify, a
temporal social network visualisation approach
designed to provide historians with a nuanced and
sophisticated view of their networks over time and
by individual actor. It deconstructs the complexity of
the network to present a simplified view for
historians to explore. In addition, it provides
information and raises questions that would not be
seen when using static social network analysis.
Further work aims to enhance the exploratory
tools available in Matrixify. In particular, further
statistical tools and layouts, such as measures of
centrality, will be included in both the temporal and
directed graph visualisations. In addition, the
questions raised by the case study are currently
being explored by historians to form part of a wider
project in the analysis of eighteenth-century business
networks. Matrixify has demonstrated that a simple
social network view can provide a wealth of
information for the historian to enhance their
understanding of the actors identified in their data
sets.
REFERENCES
Abello, J., Korn, J., 2002. MGV: A System for Visualizing
Massive Multigraphs. In IEEE Transactions on
Visualization and Computer Graphics 8(1) pp. 21-38.
Bezerianos, A., Dragicevic, P., Fekete, J.-D., Juhee Bae,
Watson, B., 2010. In IEEE Transactions on
Visualization and Computer Graphics, 16(6) pp. 1073-
1081.
Burt, R. D., 2004. Structural Holes and Good Ideas. In
American Journal of Sociology, 10(2) pp. 349-399.
Carlos, A. M., Maguire, K., Neal, L., 2008. ‘A Knavish
People…’: London Jewry and the Stock Market
During the South Sea Bubble. In Business History
50(6) pp. 728-748.
Churchill, E. F., Halverson, C. A., 2005. Social Networks
and Social Networking. In IEEE Internet Computing
Sep/Oct 2005 pp. 14-19.
Company, 1750-1810. Minute Book of the African
Merchants Trading from Liverpool, unpublished,
Liverpool Record Office 352/MD1.
Erikson, E., Bearman, P., 2006. Malfeasance and the
Foundations for Global Trade: The Structure of
English Trade in the East Indies, 1601-1833. In
American Journal of Sociology 112(1) pp. 195-230.
Falkowski, T., Bartelheimer, J., Spiliopoulou, M., 2006.
Mining and Visualizing the Evolution of Subgroups in
Social Networks. In Proceedings of the International
Conference on Web Intelligence, Hong Kong, pp. 52-
58.
Freeman, L. C., 1978/79. Centrality in Social Networks. In
Social Networks 1 pp. 215-239.
Granovetter, M. S., 1973. The Strength of Weak Ties. In
American Journal of Sociology 78(6) pp. 1360-1380.
Haggerty, J., Haggerty, S., 2010. Visual Analytics of an
Eighteenth-Century Business Network. In Enterprise
and Society 11(1) pp. 1-25.
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