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Record Nr. |
UNINA9910253341503321 |
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Autore |
Drout Michael D.C |
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Titolo |
Beowulf Unlocked : New Evidence from Lexomic Analysis / / by Michael D.C. Drout, Yvette Kisor, Leah Smith, Allison Dennett, Natasha Piirainen |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Palgrave Macmillan, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XI, 96 p. 16 illus., 15 illus. in color.) |
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Collana |
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Disciplina |
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Soggetti |
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Language and languages - Style |
Classical literature |
Literature, Ancient |
European literature |
Stylistics |
Classical and Antique Literature |
European Literature |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Lexomic Methods -- Text Preparation of Beowulf -- Cluster Analysis of Beowulf -- Interpretation of the Cluster Analysis -- Conclusions Drawn from Cluster Analysis -- Bibliography -- Index . |
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Sommario/riassunto |
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The most original and ground-breaking work on Beowulf in several decades, this book uses “lexomic” methods that blend computer-assisted statistical analysis with traditional approaches to reveal new and surprising information about the construction and sources of the greatest surviving Old English poem. Techniques of cluster analysis identify patterns of vocabulary distribution that indicate robust similarities and differences among segments of the poem. The correlation of these patterns with knowledge gained from source-study, philological analysis, and neglected previous scholarship sheds new light on the material of which Beowulf was made and the way it was composed. The implications of this investigation for the dating, structure, and cultural context of Beowulf will overturn the current scholarly consensus and significantly improve our understanding of the |
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poem, its nature, and origins. . |
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