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167 Network Analysis and Digital Prosopography In 2009, a new digital research project, the Berkeley Prosopography Service (BPS), 533 received fund<strong>in</strong>g from the Office of Digital Humanities (ODH) of the NEH to create “an open source digital toolkit that extracts prosopographic data from TEI encoded text and generates <strong>in</strong>teractive visual representations of social networks.” 534 This project is led by Niek Veldhuis, along with Laurie Pearce and Patrick Schmitz, and they are utiliz<strong>in</strong>g NLP and social network analysis (SNA) techniques to extract personal names and family relationships of people mentioned <strong>in</strong> texts and to then assemble a social network of people based on described activities. 535 The <strong>in</strong>itial tool will be applied to a corpus 536 of approximately 700 cuneiform tablets from the CDLI that record sales and lease transactions among a small group of Mesopotamians from Uruk (southern Iraq) between 331 and 346 BC. After the Uruk text corpus 537 has been converted <strong>in</strong>to TEI-XML, prosopographic data will be automatically extracted from the TEI files, SNA techniques will be used to create various networks, and users will then be able to visualize the results <strong>in</strong> various ways: A probabilistic eng<strong>in</strong>e will collate all the person-references <strong>in</strong> the corpus, along with some basic world knowledge, like the typical length of adult activity, and will then associate the names to <strong>in</strong>dividual persons, and f<strong>in</strong>ally will relate the people to one another by the k<strong>in</strong>d of activities they engaged <strong>in</strong>. The result<strong>in</strong>g graph model can be used to produce a variety of reports and visualization tools, <strong>in</strong>clud<strong>in</strong>g simple name lists and family trees, as well as <strong>in</strong>teractive models. By <strong>in</strong>tegrat<strong>in</strong>g graph visualization tools, the project will provide <strong>in</strong>teractive tools that let researchers explore the network of associations and activities. They can focus on an <strong>in</strong>dividual, on a given type of activity (e.g., real-estate sales), or explore other aspects of the model. This should enable the researchers to answer many complex questions more easily, and with a visual response (Schmitz 2009). The BPS will provide researchers with <strong>in</strong>dividual workspaces and will be the first <strong>in</strong>dependent tool to be <strong>in</strong>corporated <strong>in</strong>to the CDLI. Dur<strong>in</strong>g the <strong>in</strong>itial grant period, beta test<strong>in</strong>g will be conducted with other corpora to test the extent to which this tool can be scaled and generalized for use <strong>in</strong> other prosopographical projects. The BPS is also participat<strong>in</strong>g <strong>in</strong> Project Bamboo as one of their demonstrators. Other work us<strong>in</strong>g network analysis 538 as a means of explor<strong>in</strong>g classical prosopography has been discussed by Graham and Ruff<strong>in</strong>i (2007). They noted that rapid developments <strong>in</strong> computer technology, particularly graph theory, provided both network analysts, and consequently prosopographers, with new tools for answer<strong>in</strong>g complex questions <strong>in</strong>volv<strong>in</strong>g the degrees of separation between network members or how densely or loosely connected networks might be: Such questions hold a natural <strong>in</strong>terest for prosopographers, who can then beg<strong>in</strong> to look for certa<strong>in</strong> characteristics—class, office, occupation, gender—and identify patterns of connectivity that they might have otherwise missed when confronted with a mass of data too large for normal synthetic approaches. And yet, network analysis has been slow to take root among 533 http://code.google.com/p/berkeley-prosopography-services/ 534 http://www.neh.gov/ODH/Default.aspxtabid=111&id=159 535 http://<strong>in</strong>ews.berkeley.edu/articles/Spr<strong>in</strong>g2009/BPS 536 The demonstrator corpus “Hellenistic Babylonia: Texts, Image and Names (HBTIN)” can be viewed at http://oracc.museum.upenn.edu/hbt<strong>in</strong>/<strong>in</strong>dex.html 537 http://cdl.museum.upenn.edu/hbt<strong>in</strong>/ 538 One of the presentations at the Digital Classicist/ICS Work <strong>in</strong> Progress Sem<strong>in</strong>ar <strong>in</strong> the summer of 2010 also exam<strong>in</strong>ed the use of network analysis <strong>in</strong> prosopography. See Timothy Hill, “After Prosopography Data Modell<strong>in</strong>g, Models of History, and New Directions for a Scholarly Genre,” http://www.digitalclassicist.org/wip/wip2010-03th.html
168 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.
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"Rome Wasn
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ii ISBN 978-1-932326-38-3 CLIR Publ
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iv EpiDoc-Based Digital Epigraphy P
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vi ABOUT THE AUTHOR Alison Babeu ha
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viii PBW PCA PDB PDL PHI PLANETS PN
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x pursuit of knowledge about the an
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2 and intellectual
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4 associations to work together, an
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6 briefly explore issues that are n
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8 for English translations of Greek
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10 is created of the entire bibliog
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12 directory of more than 2,100 cat
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14 generated by the decision tree p
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16 The image-registration algorithm
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18 Schibel and Rydberg-Cox argued t
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20 information ret
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22 In ancient manuscripts, Sanskrit
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24 algorithms; ins
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26 Markov Models (MEMM) 82 and outp
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28 One major project to recently em
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30 developed a cuneiform sign reper
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32 and prayers), and edited texts a
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34 Digital critical editions, howev
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36 While these requirements may see
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38 many discrete texts, in<
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40 examine how l<s
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42 The second fact that Rob
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44 “multimedia scholarly editions
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46 different apparatuses. In Bosche
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48 individual text
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50 In these cases we must provide a
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68 funded with public money <strong
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72 framework to in
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74 then mapped to the CRM-EH so tha
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86 transparency, accessibility, ava
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88 (Research Archive for Ancient Sc
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90 This challenge of not just digit
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92 Part of the research of the Plei
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94 After correctin
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96 Epigraphy Overview: Epigraphy Da
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98 step, because epigraphic texts s
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100 text and to previous annotation
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104 original); typ
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106 To begin this
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108 better set the in</stro
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110 Another related project that ha
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114 names in texts
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226 methods,” Cohen et al. expla<
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236 of architecture, tools and serv
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240 semantic tools that would make
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250 commercial providers. At the sa
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252 representations beyond the bord
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266 Interoperability”). 763 The m
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270 This architecture makes it easy
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272 [Aschenbrenner et al. 2008]. As
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274 Editions.” Advances i
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276 [Bodard et al. 2009]. Bodard, G
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278 [Bulger et al. 2011]. Bulger, M
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280 [Choudhury and Stin</st
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282 [Crane et al. 2009a]. Crane, Gr
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284 [Dué and Ebbott 2009]. Dué, C
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286 [Flaten 2009]. Flaten, Arne R.
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288 [Hardwick 2000]. Hardwick, Lorn
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290 Conference on E-Science Worksho
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292 [Lockyear 2007]. Lockyear, Kris
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294 Cambridge, MA: Association for
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296 [Ntzios et al. 2007]. Ntzios, K
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298 [Reddy and Crane 2006]. Reddy,
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300 [Rydberg-Cox 2009]. Rydberg-Cox
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302 [Smith 2010]. Smith, D. Neel.
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304 and the Canadian Academic Commu
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306 [Wallom et al. 2009]. Wallom, D
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