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ancient historians. Network analytical research on the Greco-Roman world has focused on
questions of religious history and topography. Nonetheless, the epigraphic and papyrological
evidence beg a network analytical approach to the prosopographical data available from these
sources (Graham and Ruff<strong>in</strong>i 2007, 325-326).
To demonstrate the value of network analysis for prosopography, the authors described their own
dissertation work. One major requirement they listed that would be needed to demonstrate the potential
of network analysis for ancient prosopography were “focused data-sets” unlike many of the massive
multivolume prosopographies such as the PLRE.
As an example of such a data set, Graham and Ruff<strong>in</strong>i described a set of data regard<strong>in</strong>g <strong>in</strong>dividuals
connected with the brick <strong>in</strong>dustry of imperial <strong>Rome</strong>. These data were largely obta<strong>in</strong>ed from bricks that
were stamped with estate and workshop names, and together the data set <strong>in</strong>cluded the names of at least
1,300 <strong>in</strong>dividuals from largely the second century AD. As <strong>in</strong>dividuals <strong>in</strong>volved <strong>in</strong> the brick <strong>in</strong>dustry
came from vary<strong>in</strong>g levels of society, the name data from the bricks have been used <strong>in</strong> various types of
historical research. Several major published catalogs of stamped bricks have been created, and Graham
created an Access database for one of them (CIL XV.1) that could be used for both archaeological and
prosopographical analysis. Numerous programs can then be used to build and analyze networks from
this data Graham and Ruff<strong>in</strong>i suggested:
In general, one simply lists the name <strong>in</strong> question and all the other names with which it cooccurs.
The programme then stitches the network together from these data. Many statistics of
use to prosopographers can then be determ<strong>in</strong>ed, but sometimes simply visualiz<strong>in</strong>g the network
itself can provide a ‘eureka’ moment. Some networks will have a number of ‘hubs’ and
everyone else is connected like a ‘spoke’; other networks will look more like a cha<strong>in</strong> with
<strong>in</strong>terlock<strong>in</strong>g circles of <strong>in</strong>dividuals. This is profoundly important (Graham and Ruff<strong>in</strong>i 2007,
328).
Graham consequently used network analysis to explore “small world” networks with<strong>in</strong> <strong>Rome</strong> and the
effect of purges and proscriptions on this network.
Another potential use of network analysis for prosopographical research listed by Graham and Ruff<strong>in</strong>i
was for “explor<strong>in</strong>g the <strong>in</strong>teractions between various cliques and clusters with<strong>in</strong> a social network” on
the level of <strong>in</strong>dividual villages, such as those described <strong>in</strong> documentary archives of papyri that survive
for a number of villages. They noted that the large number of papyrological databases such as APIS
and DDbDP provide a wealth of material that can be m<strong>in</strong>ed for prosopographical analysis or, as they
call it, “a prosopographical growth <strong>in</strong>dustry with enormous potential.” The dissertation work of Ruff<strong>in</strong>i
used network analysis with documentary papyri from the Aphrodito archive to explore the prom<strong>in</strong>ence
of <strong>in</strong>dividuals other than the heavily studied Dioskoros and his family. Ruff<strong>in</strong>i suggested that network
analysis provides a number of “centrality measures,” such as “closeness centrality” and “betweenness
centrality,” that can be used to “identify the most central figures <strong>in</strong> the archive, measures whose
quantitative nature hopefully removes the biases <strong>in</strong>troduced by our own scholarly curiosity and
prejudice.” Us<strong>in</strong>g these two measures identified three other prom<strong>in</strong>ent <strong>in</strong>dividuals, results that
surprised him as none of them is mentioned <strong>in</strong> modern scholarship on Aphrodito. A f<strong>in</strong>al potential use
of network analysis for prosopography illustrated by Graham and Ruff<strong>in</strong>i was the analysis of
occupational groups and the social connectivity between them.