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Gentil-Beccot, Anne; Mele, S.; Holtkamp, Annette; O'Connell, Heath Bland; Brooks, Travis C.

doi:10.1002/asi.v60:1

Cited by 113 publications

(4 citation statements)

References 536 publications

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“…(Sebastiani, 2002), but also for authorship attribution, classification of texts according to their authors' gender, age, provenance, and more (Koppel et al, 2009). This methodology has been successfully applied to studying O vs. T in various datasets and in different source and target languages (see Section 2).…”

Section: Introductionmentioning

confidence: 99%

On the features of translationese

Volansky

Ordan

Wintner

2013

Digital Scholarship in the Humanities

104

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Much research in translation studies indicates that translated texts are ontologically different from original, non-translated ones. Translated texts, in any language, can be considered a dialect of that language, known as 'translationese'. Several characteristics of translationese have been proposed as universal in a series of hypotheses. In this work we test these hypotheses using a computational methodology that is based on supervised machine learning. We define several classifiers that implement various linguistically-informed features, and assess the degree to which different sets of features can distinguish between translated and original texts. We demonstrate that some feature sets are indeed good indicators of translationese, thereby corroborating some hypotheses, whereas others perform much worse (sometimes at chance level), indicating that some 'universal' assumptions have to be reconsidered.

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Section: Introductionmentioning

confidence: 99%

On the features of translationese

Volansky

Ordan

Wintner

2013

Digital Scholarship in the Humanities

104

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“…The data was collected from ISI Web of Science. This source has been used by multiple scholars (e.g., Cronin, 2001;Harzing & Wal, 2009;Peng & Zhou, 2006) and is among the most complete, including documents going as far back as 1900 from over 12,000 journals (Thomson Reuters, 2014).…”

Section: Methodsmentioning

confidence: 99%

A Bibliometric Study on Culture Research in International Business

Pinto

Serra

Ferreira

2014

BAR, Braz. Adm. Rev.

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National cultures and cultural differences provide a crucial component of the international business (IB) research context. We conducted a bibliometric study of articles published in seven leading IB journals over a period of three decades to analyze how national culture has been impacting IB research. Co-citation mappings permit us to identify the ties binding works dealing with culture and cultural issues in IB. We identify two main clusters of research, each comprising two sub-clusters, with Hofstede's (1980) work delineating much of the conceptual and empirical approach to culture-related studies. One main cluster entails works on the conceptualization of culture and its dimensions and the other cluster focuses on cultural distance. This conceptual framework captures the extant IB research incorporating culture-related concepts and influences.

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“…One particularly relevant area is that of compositor attribution-the clustering of pages in a historical printed document by the individual (the compositor) who set the type. Like stylometry, a long-standing area of NLP that has largely focused on attributing the authorship of text (Holmes, 1994;Hope, 1994;Juola, 2006;Koppel et al, 2009;Jockers and Witten, 2010), the analysis of orthographic patterns is fundamental to compositor attribution. Additionally, compositor attribution often makes use of visual features, such as whitespace layout, introducing new challenges.…”

Section: Introductionmentioning

confidence: 99%

Automatic Compositor Attribution in the First Folio of Shakespeare

Ryskina

Alpert-Abrams

Garrette

et al. 2017

Proceedings of the 55th Annual Meeting of the Association For Computational Linguistics (Volume 2: Short Papers)

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Compositor attribution, the clustering of pages in a historical printed document by the individual who set the type, is a bibliographic task that relies on analysis of orthographic variation and inspection of visual details of the printed page. In this paper, we introduce a novel unsupervised model that jointly describes the textual and visual features needed to distinguish compositors. Applied to images of Shakespeare's First Folio, our model predicts attributions that agree with the manual judgements of bibliographers with an accuracy of 87%, even on text that is the output of OCR.

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Untitled

Cited by 113 publications

References 536 publications

On the features of translationese

On the features of translationese

A Bibliometric Study on Culture Research in International Business

Automatic Compositor Attribution in the First Folio of Shakespeare

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