Abstract
Geographical and social networks form a broad and fashionable yet important field of research in archaeology and geography. Networks are tightly connected to the mathematical graph theory. This chapter starts by discussing the concepts of network and transportation systems, before we focus on transportation networks. On a local, level pathways are constructed using least cost path analysis and reconstructed using pattern recognition. The combination of the constructed theoretical and reconstructed empirical model serves not only to set up an integrative model of the transport system but also to establish knowledge about social behaviour. The regional level does not deal with the exact location of the pathways but rather with the connection between places. Methods from graph theory are used as both empirical and theoretical models of the structure of transport system. Finally, the characterisation of both networks and elements in networks is addressed, serving as a basis for the comparison of networks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barthélemy, M. (2014). Discussion: Social and spatial networks. Nouvelles de l’archéologie, 135, 51–61.
Bivand, R. S., Pebesma, E. J., & Gómez-Rubio, V. (2008). Applied spatial data analysis with R. New York: Springer.
Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92, 1170–1182.
Borgatti, S. P. (2005). Centrality and network flow. Social Networks, 27, 55–71.
Bourgeois, Q. (2013). Monuments on the Horizon. The formation of the barrow landscape throughout the 3rd and 2nd millennium BC. Leiden: Sidestone Press.
Brandes, U., Robins, G., McCranie, A., & Wasserman, S. (2013). What is network science? Network Science, 1, 1–15.
Brughmans, T. (2010). Connecting the dots: Towards archaeological network analysis. Oxford Journal of Archaeology, 29, 277–303.
Brughmans, T. (2013). Thinking through networks: A review of formal network methods in archaeology. Journal of Archaeological Method and Theory, 20, 623–662.
Brughmans, T., Keay, S., & Earl, G. P. (2013). Understanding inter-settlement visibility in Iron Age and Roman Southern Spain with exponential random graph models for visibility networks. Journal of Archaeological Method and Theory, 22, 1–32.
Chen, G., Gould, R. J., Jacobson, M. S., Schelp, R. H., & West, D. A. (1992). A characterization of influence graphs of a prescribed graph. Vishwa International Journal of Graph Theory, 1, 77–81.
Collar, A., Coward, F., Brughmans, T., & Mills, B. J. (2015). Networks in archaeology: Phenomena, abstraction, representation. Journal of Archaeological Method and Theory, 22, 1–32.
Delaunay, B. N. (1934). Sur la sphère vide. Bulletin of the Academy of Sciences of the USSR, 7(6), 793–800.
Diestel, R. (2000). Graph theory. New York: Springer.
van Etten, J. (2015). R Package gdistance: Distances and routes on geographical grids. Journal of Statistical Software, 10, 1–22.
Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40, 35–41.
Freeman, L. C. (1978/1979). Centrality in social networks - conceptual clarification. Social Networks, 1, 215–239.
Fulminante, F. (2014). The network approach: Tool or paradigm? Archaeological Review from Cambridge, 29, 167–178.
Granovetter, M. S. (1973). The strength of weak ties. The American Journal of Sociology, 78, 1360–1380.
Haggett, P. (1965). Locational analysis in human geography. London: Arnold.
Haggett, P. (1970). Network models in geography. In R. J. Chorley & P. Haggett (Eds.), Integrated models in geography (pp. 609–668). London: Methuen.
Haggett, P., & Chorley, R. J. (1969). Network analysis in geography. London: Arnold.
Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. University of California, Riverside, Department of Sociology, Riverside, CA: Digitalpublikation. http://faculty.ucr.edu/~hanneman/nettext/.Cited18Feb2014.
Helbing, D., Keltsch, J., & Molnár, P. (1997). Modelling the evolution of human trail systems. Nature, 388, 47–50.
Herzog, I. (2013). Theory and practice of cost functions. In F. Contreras, M. Farjas & F. J. Melero (Eds.), Fusion of cultures. Proceedings of the 38th Annual Conference on Computer Applications and Quantitative Methods in Archaeology, Granada, Spain, April 2010. BAR International Series, Vol. 2494. (pp. 375–382).
Herzog, I. (2013). Potential and limits of optimal path analysis. In A. Bevan & M. Lake (Eds.), Computational approaches to archaeological spaces (pp. 179–211). Walnut Creek, CA: Left Coast Press.
Herzog, I. (2014). Least-cost paths - some methodological issues. Internet Archaeology, 36. http://dx.doi.org/10.11141/ia.36.5.
Knappett, C. (2011). An archaeology of interaction: Network perspectives on material culture and society. Oxford: Oxford University Press.
Knappett, C. (Ed.). (2013). Network analysis in archaeology: New approaches to regional interaction. Oxford: Oxford University Press
Koschützki, D., Lehmann, K. A., Peeters, L., Richter, S., Tenfelde-Podehl, D., & Zlotowski, O. (2005). Centrality indices. In U. Brandes & T. Erlebach (Eds.), Network analysis (pp. 16–61). Berlin: Springer.
Koschützki, D., Lehmann, K. A., Tenfelde-Podehl D., & Zlotowski, O. (2005). Advanced centrality concepts. In U. Brandes & Erlebach, T. (Eds.), Network analysis (pp. 83–111). Berlin: Springer.
Llobera, M. (2000). Understanding movement: A pilot model towards the sociology of movement. In G. Lock (Ed.), Beyond the Map. Archaeology and Spatial Technologies (pp. 65–84). Amsterdam, Berlin, Oxford, Tokyo, Washington DC: IOS Press.
Michael, T. S., & Quint, T. (1999). Sphere of influence graphs in general metric spaces. Mathematical and Computer Modelling, 29, 45–53.
Moreno, J. L. (1934). Who shall survive? Washington, DC: Nervous and Mental Disease Publishing Company.
Müller, S. (1904). Vei og Bygd i Sten- og Bronzealdern. Aarbøger for Nordisk oldkyndighed og historie, 1904, 1–64.
Müller, U. (2012). Networks of towns’ networks of periphery? Some relations between the North European Medieval town and its hinterland. In S. Brather, U. Müller & H. Steuer (Eds.), Raumbildung durch Netzwerke? Der Ostseeraum zwischen Wikingerzeit un Spaetmittelalter aus archaeologischer und geschichtswissenschaftlicher Perspektive (pp. 55–78). Bonn: Dr. Rudolf Habelt GmbH.
Nakoinz, O. (2012). Ausgewählte Parameter der Lage von Wegen und Monumenten als Proxy für soziale Prozesse prähistorischer Gesellschaften. In M. Hinz & J. Müller (Eds.), Siedlung, Grabenwerk, Großsteingrab. Studien zu Gesellschaft, Wirtschaft und Umwelt der Trichterbechergruppen im nördlichen Mitteleuropa: Vol. 2. Frühe Monumentalität und soziale Differenzierung (pp. 445–456). Bonn: Habelt.
Nakoinz, O. (2013). Archäologische Kulturgeographie der ältereisenzeitlichen Zentralorte Südwestdeutschlands: Vol. 224. Universitätsforschung zur Prähistorischen Archäologie. Bonn: Habelt.
Newman, M. E. J. (2010). Networks: An introduction. Oxford: Oxford University Press.
Nuhn, H., & Hesse, M. (2006). Verkehrsgeographie. Paderborn: Schöningh.
Ortúzar, J. de D., & Willumsen, L. G. (2011). Modelling transport. Chichester: Wiley.
Peuker, T. K., & Douglas, D. H. (1975). Detection of surface-specific points by local parallel processing of discrete terrain elevation data. Computer Graphics and Image Processing, 4, 375–387.
Prömel, H. J., & Steger, S. (2002). The Steiner tree problem. A tour through graphs, algorithms, and complexity. Braunschweig: Vieweg.
Ramachandran, S., & Rosenberg, N. A. (2011). A test of the influence of continental axes of orientation on pattern sof human gene flow. American Journal of Physical Anthropology, 146, 515–529.
Scott, J. (1991). Social network analysis: A handbook. London: Sage.
Sindbæk, S. M. (2007). Networks and nodal points: The emergence of towns in early viking age Scandinavia. Antiquity, 81, 119–132.
Taaffe, E. J., Gauthier, H. L., & O’Kelly, M. E. (1973). Geography of transportation. Upper Saddle River: Prentice Hall.
Toussaint, G. T. (1980). Pattern recognition and geometric complexity. In Proceedings of the 5th International Conference on Pattern Recognition (pp. 1324–1347). Miami Beach, FL.
Toussaint, G. T. (1980). The relative neighborhood graph of a finite planar set. Pattern Recognition, 12, 261–268.
Toussaint, G. T. (1981). Computational geometric problems in pattern recognition. In J. Kittler (Ed.), Pattern recognition theory and applications (pp. 73–91). Oxford: NATO Advanced Study Institute, Oxford University Press.
Toussaint, G. T. (2014). The sphere of influence graph: Theory and applications. International Journal of Information Technology & Computer Science, 14, 2091–1610.
Tremblay-Cormier, L. (2014). Le mobilier métallique méditerranéen comme témoin des échanges à longue distance entre Rhin et Rhôe, du 10ème au 5ème siècle avant notre ère. In P. Barral, J.-P. Guillaumet, M.-J. Roulière-Lambert, M. Saracino & D. Vitali (Eds.), Les Celtes en Italie, May 2012 (pp. 297–309). Verone, Italy: Société archéologique de l’Est.
Urquhart, R. B. (1980). Algorithms for computation of relative neighborhood graph. Electronics Letters, 16, 556–557.
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press, pp. 58–143.
White, D. A., & Surface-Evans, S. (Eds.). (2012). Lest cost analysis of social landscapes. Ann Arbor: The University of Uta Press.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Nakoinz, O., Knitter, D. (2016). Networks. In: Modelling Human Behaviour in Landscapes. Quantitative Archaeology and Archaeological Modelling . Springer, Cham. https://doi.org/10.1007/978-3-319-29538-1_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-29538-1_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29536-7
Online ISBN: 978-3-319-29538-1
eBook Packages: Behavioral Science and PsychologyBehavioral Science and Psychology (R0)