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Text Mining pp 87–112Cite as

Towards a Network Model of the Coreness of Texts: An Experiment in Classifying Latin Texts Using the TTLab Latin Tagger

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Abstract

The analysis of longitudinal corpora of historical texts requires the integrated development of tools for automatically preprocessing these texts and for building representation models of their genre- and register-related dynamics. In this chapter we present such a joint endeavor that ranges from resource formation via preprocessing to network-based text representation and classification. We start with presenting the so-called TTLab Latin Tagger (TLT) that preprocesses texts of classical and medieval Latin. Its lexical resource in the form of the Frankfurt Latin Lexicon (FLL) is also briefly introduced. As a first test case for showing the expressiveness of these resources, we perform a tripartite classification task of authorship attribution, genre detection and a combination thereof. To this end, we introduce a novel text representation model that explores the core structure (the so-called coreness) of lexical network representations of texts. Our experiment shows the expressiveness of this representation format and mediately of our Latin preprocessor.

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Notes

  1. 1.

    According to Anne Bohnenkamp-Renken, Goethe-House Frankfurt, personal communication.

  2. 2.

    TTLab is an acronym that denotes the Frankfurt Text-technology lab (www.hucompute.org).

  3. 3.

    The FLL results from a cooperation of historians and computer scientists—see the project website for more information: www.comphistsem.org.

  4. 4.

    collex.hucompute.org.

  5. 5.

    archives.nd.edu/whitaker/dictpage.htm.

  6. 6.

    ramminger.userweb.mwn.de.

  7. 7.

    la.wiktionary.org/wiki/Pagina_prima.

  8. 8.

    Provided by Michael Trauth, Trier University. See also [36].

  9. 9.

    collex.hucompute.org. is our interface for this human computation of a Latin resource.

  10. 10.

    www.dmgh.de/de/fs1/object/display/bsb00000820_meta:titlePage.html?sortIndex=020:030:0001:010:00:00.

  11. 11.

    By the members of Bernhard Jussen’s lab at Goethe-University Frankfurt: Silke Schwandt, Tim Geelhaar, and colleagues.

  12. 12.

    la.wiktionary.org/wiki/Pagina_prima

  13. 13.

    Models of text representation as small as the one introduced here are common in quantitative text linguistics—an early example is [40]. The difference is that while these models mostly consider well-established indices like TTR or the rate of hapax legomena, we are concerned with inventing a complete new set of quantitative text characteristics based on the same notion of text organization.

  14. 14.

    A test of this hypothesis will be the object of a forthcoming paper.

  15. 15.

    Obviously, for any v: u(v) ≥ σ(v).

  16. 16.

    For linguistic indicators of the monastic-scholastic distinction see [57, 58].

  17. 17.

    The underlying texts of this corpus have been selected by Silke Schwandt from the Patrologia Latina [17]. They are accessible via the eHumanities Desktop (hudesktop.hucompute.org).

  18. 18.

    Note that this goal also requires a semantic disambiguation and sense tagging [61]—beyond PoS tagging— which is not yet provided by the TLT.

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Acknowledgements

Financial support by the BMBF-project Computational Historical Semantics (www.comphistsem.org) as part of the research center on Digital Humanities is gratefully acknowledged. We also thank both anonymous reviewers for their valuable hints, Barbara Job and Silke Schwandt for their fruitful hints on distinguishing monastic and scholastic texts and, finally, Andy Lücking for assisting in producing TikZ graphics.

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  1. Goethe-University Frankfurt, Frankfurt, Germany

    Alexander Mehler, Tim vor der Brück, Rüdiger Gleim & T. Geelhaar

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  1. Alexander Mehler
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Correspondence to Alexander Mehler .

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  1. Computer Science Department, Technische Universität Darmstadt FG Language Technology, Darmstadt, Germany

    Chris Biemann

  2. Computer Science Department, Goethe University WG Text Technology, Frankfurt am Main, Hessen, Germany

    Alexander Mehler

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Mehler, A., vor der Brück, T., Gleim, R., Geelhaar, T. (2014). Towards a Network Model of the Coreness of Texts: An Experiment in Classifying Latin Texts Using the TTLab Latin Tagger. In: Biemann, C., Mehler, A. (eds) Text Mining. Theory and Applications of Natural Language Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-12655-5_5

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