Mining Citations, Linking Texts
Published in ISAW Papers 7, 2014
Romanello, Matteo (2014). “Mining Citations, Linking Texts.” ISAW Papers 7. http://dlib.nyu.edu/awdl/isaw/isaw-papers/7/romanello/.
Canonical citations are the standard way of citing primary sources (i.e., the ancient texts) in Classics: the ability to read them, which requires knowing what numerous abbreviations stand for, is part of the early training of any classicist. Having an expert system to capture automatically these citations and their meaning is one of the aims of the project of which the research presented in this paper is part. The desire for such a system has existed for a considerable amount of time (Crane, Seales, and Terras 2009, 26) but has yet to be solved (Romanello, Boschetti, and Crane 2009; Romanello 2013). Such a system has great potential both for scholars in Classics and for the study of Classics as a discipline: capturing the citations of ancient texts that are contained in journal articles, commentaries, monographs and other secondary sources, allows us, for example, to track over time how and how often texts were studied, essential pieces of information for a data-driven study of the discipline and its evolution. Another possible use of the system is to display related bibliographic references within a reading environment for ancient texts. The examples that are used in this paper are taken from work that has been done to provide the GapVis interface of the Hellespont project1 with such a functionality (see Fig. 1). One of the goals of the project is to create an enhanced virtual reading environment for one specific section of Thucydides’ Histories, the so-called “Pentecontaetia” (Thuc. 1,89 to 1,118). The references that are displayed in the secondary literature view of the reading interface are mined automatically from JSTOR and are shown together with links to the full text of the journal article as well as to the cited passage in the Perseus digital library (Romanello and Thomas 2012).
Recommended citation: Romanello, Matteo (2014). “Mining Citations, Linking Texts.” ISAW Papers 7.