This document summarizes a student project that used network analysis to study Bronze Age social networks through the distribution of pottery related to feasting activities. The project goals were to use digital methods and network analysis to explore how feasting contributed to social stratification. Data on pottery vessels from 10 archaeological sites was collected and analyzed using Gephi software. The network analysis identified modules and high centrality pottery types linking sites. It provided insights into the emergence of social hierarchy in Bronze Age chiefdoms through conspicuous consumption during feasting events.

1. Colloquium on Digital History and the Transnational
History of Nursing
Eat, Drink and Be Networked:
Feasting and Bronze Age Networks
Zack Batist
Directed Interdisciplinary Studies
Faculty Supervisor, Dr. Shawn Graham
March 23, 2012

2. Project Goals
• To learn how design, implement and interpret
the results of projects that utilize digital
components and methodologies
• To explore the use of network analysis in an
archaeological setting
• To study how the consumption of intoxicating
substances contributed to the social
stratification of early societies
• This was accomplished by studying the
distribution of pottery relating to feasting
across the Bronze Age Aegean

3. The Emergence of a
Social Hierarchy
• The presence of luxury vessels that were reserved for the activities
of the wealthy would signify the presence of an upper class, who
mobilized resources and oversaw the centralized economies of
this setting
• The middle/late Bronze Age was a period of transition from a
more-or-less egalitarian society to an increasingly hierarchical
chiefdom structure with an elite class.
• Feasting is an interesting example of conspicuous
consumption, through which the leader reinforced his leadership
and links to the his allies, while also emphasizing his distinction
from the rest of the community.

4. National Archaeological Museum, Athens

5. Network Analysis in Archaeology and the Social
Sciences
• Network analysis is a method to find relationships
between entities that are not plainly obvious.
• This set of methods is especially useful in
archaeology, since the accumulation of intertwined
data is difficult to analyze and interpret
• It provides a systematic approach to examine social
relationships in a quantitative way.
• Network analysis can be used to examine the
relationships between any kinds of variables
• In the social sciences, interpretation requires the
consideration of the nature of what nodes actually
represent
• When working with objects, they must mean
something to the people who used them

6. Dataset
• Individual vessels were recorded from excavation reports
– Problems included uneven depths of excavations, limited access to reports
• Total of 5669 vessels were recorded
– Of them, 2995 vessels were included in the analysis.
• Ten sites were included in the analysis
• Variations within a pottery type were ‘lumped’ together
• Luxury pottery is easily classifiable by function to the activities of the
elite within a hierarchal society.

7. Computational Methods
• Gephi – www.gephi.org.
• Metrics used:
• Degree - The degree represents the number of connections that a particular
node is directly associated with.
• Betweeness Centrality - The betweeness centrality is the measure of how
often a particular node acts as an intermediary between the pats of any two
other nodes in a given network. This is usually expressed as an index value.
• Modularity - This metric identifies small sub-communities of nodes within the
overall network. Densely packed groupings are often connected with less
dense intermediaries. In social network analysis, the identification of these
sub-communities often reflect real-world applications.
Ulrik Brandes, “A Faster Algorithm for Betweenness Centrality,” The Journal of Mathematical Sociology 25, no. 2 (2001): 163–177.
Vincent D Blondel et al., “Fast Unfolding of Communities in Large Networks,” Journal of Statistical Mechanics: Theory and Experiment
2008, no. 10 (October 9, 2008): P10008.

8. Ariadne Algorithm
• Developed by Evans, Rivers and Knappet
• Applied to 34 Bronze Age locations of the Aegean
• Included factors that ‘push’ or ‘pull’ people to travel to certain
sites
– Access to resources, population dynamics, carrying capacity
• Also incorporates wind and sea currents, sailing technology
and physical location
• Tim Evans, Ray Rivers and Carl Knappett, “Interactions in Space for Archaeological Models,”
2011
• Carl Knappett, Tim Evans, and Ray Rivers, “Modelling Maritime Interaction in the Aegean
Bronze Age,” Antiquity 82, no. 318 (2008): 1009–1024.

9. Two-Mode Network (Pottery – Sites)

10. One-Mode Network (Pottery)
• Displays the relationships
between luxury pottery types,
based on their co-presence at
various archaeological sites
• Two separate modules are
displayed
• Alabastron & Stirrup jar have
high centrality values and link
these distinct communities

11. One-Mode Network (Sites)
• Displays the relationships
between archaeological
sites based on which luxury
pottery types were found at
each one
• No luxury vessels at
Amorgos, according to this
dataset

12. Some Key Lessons Concerning Network
Analysis in the Social Sciences
• It is very important to establish goals early on
• Data collection must suit these goals
• Good quality data is crucial, since the analysis and
interpretation are dependent on it
• If the interpretations are of social interactions, the dataset
must be representative of this
– Artifacts must mean something to the people who used them
• The digital humanities are about extending the reach of
traditional methods of academic research by using
technology, working in an interdisciplinary
environment, facilitating collaboration with other
scholars, and the publication of results in an open and

13. Thank You!
Merci!