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Trees into Nets: Network-based Approaches to Ancient Greek Treebanks

Francesco Mambrini and Marco Passarotti

(Additional presenter: Marco Passarotti Università Cattolica del Sacro Cuore, Milan)

"Networks"  are  rapidly  evolving  into  the  dominating  model  for  scientific  knowledge. Networks -­ it has been argued -­ "will drive the fundamental questions that form our view of the world in the coming era" [1: 7].

Very recently, linguistics too has been touched by this paradigm shift. Graphs based on synonyms or co-­occurring words (where words are the nodes, and the proximity in a given text  creates links between them) were compared to the complex networks studied in computer  sciences, physics or sociology [2]. Yet co-­occurrence is only a superficial phenomenon, that hardly account for the structure of a language. By encoding information on  the  syntactic  relations  between  each  word,  dependency  treebanks can drastically improve the quality of the available resources for network analysis [3, 4, 5].

In our talk, we will apply this new approach to the domain of Ancient Greek literary texts for the first time. We will take our data from the Ancient Greek Dependency Treebank (AGDT) and PROIEL, two dependency-­based treebanks that include texts from the Archaic and Classical age with complete morpho-­syntactic annotation. Networks where the nodes are represented  by  the  lemmata,  and  the  dependency  relations  between  them  are  the (directed) edges will be generated from a subset of these collections. Difficult authors such as Sophocles (fig. 1) and Aeschylus (from the AGDT) will be analyzed using the standard metrics that are employed to describe the structure of a network (its topology): average path length, clustering coefficient, and degree distribution [4].

The observations on the tragic poets will be compared with a similar network based on a contemporary prose author (Herodotus), whose text is partially annotated in PROIEL.

We will discuss whether even the difficult text of the Greek tragic poets comply with the model of small-­world, highly clustered networks that is commonly observed in physics or sociology [1, 3, 4]. At the same time, our analysis will serve to open other questions that are crucial for the field of Classics and the Humanities. What are the peculiarities of a network  representing  literary  works?  What  word-­classes  play  the  role  of  the  highly connected "hubs"? And ultimately, can this approach tell us anything about the language or the style of a work?

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Making Meaning from Data

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