Abstract
The initial results of hierarchical agglomerative cluster analysis of segments of Beowulf show a heterogeneity of vocabulary distribution. Techniques of screening, shifting and blending are used to identify robust segment boundaries. The text copied by the A-Scribe is analyzed separately from that copied by the B-Scribe, producing two “scrabble diagrams” of the similarities and differences among segments. The normalized text is then used to analyze the A- and B-Scribe texts together, identifying the boundaries of the segment divided between the two scribes and demonstrating similarities among segments in both parts of the poem.
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Drout, M.D.C., Kisor, Y., Smith, L., Dennett, A., Piirainen, N. (2016). Cluster Analysis of Beowulf . In: Beowulf Unlocked. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-30628-5_4
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DOI: https://doi.org/10.1007/978-3-319-30628-5_4
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Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-319-30627-8
Online ISBN: 978-3-319-30628-5
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