Articles from Digital Scholarship in the Humanities (formerly LLC)

Accessing Russian culture online: The scope of digitization in museums across Russia

AbstractWe compare the scope of museum digitization in the Russian Federation, a country with diverse cultural heritage and over 2,300 museums, with the scope of digitization in Europe as measured by the Enumerate Survey of 355 museums from twenty European countries initiated by the Collections Trust, UK, in 2011. Our article shows that the reach and scope of digitization in Russia is lesser than that of European museums. Digitization is mainly done in Russia for inventory purposes.

Towards a new approach in the study of Ancient Greek music: Virtual reconstruction of an ancient musical instrument from Greek Sicily

AbstractIn the summer of 2012, the Institute of Fine Arts, New York University Selinunte Mission began to explore the interior of the cella of Temple R. This excavation showed that the classical and archaic layers had been sealed by a deep fill of the Hellenistic period and left untouched by earlier archaeological research at the site. Among the discoveries were a series of votive depositions positioned against the walls, dating to the sixth century BCE.

‘he liked to read, write, and whatch televishon’—The APU Writing and Reading Corpus (1979–1988)

AbstractRecent research has demonstrated the potential of corpus linguistics as a solid aid in children’s understanding of how language works. However, the availability of data from the UK is still somewhat limited. Most corpora are either based on a small number of schools, synchronic in nature, or focused on the post-National Curriculum era (cf. Lancaster Corpus of Children’s Project Writing, the Oxford Children’s Corpus, the Growth in Grammar Corpus); on the other hand, historical corpora are, unfortunately, not publicly available in electronic format (cf.

An improvement to Zeta

AbstractZeta has been described as ‘the most powerful general-purpose authorship tool currently available.’ It has been used to attribute parts of Arden of Faversham to Shakespeare and parts of 3 Henry VI to Marlowe, among other uses. The method was invented by John Burrows, but it is currently used in an adapted form developed by Hugh Craig. This article demonstrates that the method has not been adapted into its simplest form, thereby obscuring a true understanding of what it does.

Quantitative Historical Linguistics: A Corpus Framework (Oxford Studies in Diachronic and Historical Linguistics). Gard B. Jenset and Barbara McGillivray

Quantitative Historical Linguistics: A Corpus Framework (Oxford Studies in Diachronic and Historical Linguistics). JensetGard B. and McGillivrayBarbara. New York: Oxford University Press, 2017. xiii +288 pp. ISBN 978-0-19-871817-8. $85.00 (hardback).

Forensic stylometry

AbstractThe R Stylo program features, Rolling Delta and Rolling Classify, were applied to Thomas Kyd’s closet drama Cornelia. After the elimination of a large number of unsuitable reference texts, Marlowe’s Tamburlaine 1 turned out to be the play with the lowest delta values; that is it showed the smallest stylistic difference from Cornelia. In previous investigations the anonymous play The Tragedy of Locrine had been identified as a play by Christopher Marlowe (see Appendix).

The interpretation of Zeta test results

AbstractZeta has been described as the most powerful general-purpose authorship tool currently available. It is therefore of the utmost importance that Zeta test results be correctly interpreted, because incorrect interpretations can lead to incorrect authorship attributions. This article argues that the current method of interpreting Zeta results, pioneered by Craig and Kinney in Shakespeare, Computers, and the Mystery of Authorship and used in the Authorship Companion to The New Oxford Shakespeare, is unsound.

Katibeh: A Persian news summarizer using the novel semi-supervised approach

AbstractNowadays, text summarization is one of the most important active research fields in information retrieval. The most of the supervised extractive summarization systems utilize learning-to-rank methods to score sentences according to their importance. They need a high-quality comprehensive summarization corpus, which is labeled manually by human experts. Unfortunately, this sort of corpus is not available for most low-resource languages such as Persian.

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