Metaphor in usage

Steen, Gerard J.; Dorst, Aletta G.; Herrmann, J. Berenike; Kaal, Anna; Krennmayr, Tina

doi:10.1515/cogl.2010.024

Cited by 164 publications

(76 citation statements)

References 13 publications

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“…The scalar system was evaluated on the VU Amsterdam Metaphor Corpus (Steen, et al, 2010) which consists of 200,000 words from the British National Corpus divided into four genres (academic, news, fiction, and spoken; performance on the spoken genre was not evaluated for this task because it consists of many short fragmentary utterances) and manually annotated for metaphor by five raters. Previous evaluations using this corpus (Dunn, 2013b) concluded that prepositions annotated as metaphoric in the corpus should not be considered metaphoric for computational purposes.…”

Section: Discussionmentioning

confidence: 99%

“…The most comprehensive noncomputational study of metaphoric expressions in large corpora (Steen, et al, 2010) found that up to 18.5% of words in the British National Corpus were used metaphorically. This means that metaphorically used words not only have very different interpretations than literally used words, but they are also common enough to pose a significant challenge for computational linguistics.…”

Section: Introductionmentioning

confidence: 99%

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Measuring metaphoricity

Dunn¹

2014

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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This paper presents the first computationally-derived scalar measurement of metaphoricity. Each input sentence is given a value between 0 and 1 which represents how metaphoric that sentence is. This measure achieves a correlation of 0.450 (Pearson's R, p <0.01) with an experimental measure of metaphoricity involving human participants. While far from perfect, this scalar measure of metaphoricity allows different thresholds for metaphoricity so that metaphor identification can be fitted for specific tasks and datasets. When reduced to a binary classification evaluation using the VU Amsterdam Metaphor Corpus, the system achieves an F-Measure of 0.608, slightly lower than the comparable binary classification system's 0.638 and competitive with existing approaches.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measuring metaphoricity

Dunn¹

2014

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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“…Biber 2011, Mahlberg 2013, but also more advanced statistical procedures such as multi-dimensional analysis in register variation (e. g., Biber 1988). These measures allow identifying non-coincidental, i. e. statistically significant, associations and frequency clusters (for a quantitative cross-register comparison of metaphor across word classes in English, see Steen et al 2010), and they facilitate quantitative variation perspectives as well as qualitative ones.…”

Section: A New Definition Of Stylementioning

confidence: 99%

Revisiting Style, a Key Concept in Literary Studies

Herrmann¹,

Dalen-Oskam²,

Schöch³

2015

Journal of Literary Theory

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Language and literary studies have studied style for centuries, and even since the advent of ›stylistics‹ as a discipline at the beginning of the twentieth century, definitions of ›style‹ have varied heavily across time, space and fields. Today, with increasingly large collections of literary texts being made available in digital form, computational approaches to literary style are proliferating. New methods from disciplines such as corpus linguistics and computer science are being adopted and adapted in interrelated fields such as computational stylistics and corpus stylistics, and are facilitating new approaches to literary style.The relation between definitions of style in established linguistic or literary stylistics, and definitions of style in computational or corpus stylistics has not, however, been systematically assessed. This contribution aims to respond to the need to redefine style in the light of this new situation and to establish a clearer perception of both the overlap and the boundaries between ›mainstream‹ and ›computational‹ and/or ›empirical‹ literary stylistics. While stylistic studies of non-literary texts are currently flourishing, our contribution deliberately centers on those approaches relevant to ›literary stylistics‹. It concludes by proposing an operational definition of style that we hope can act as a common ground for diverse approaches to literary style, fostering transdisciplinary research.The focus of this contribution is on literary style in linguistics and literary studies (rather than in art history, musicology or fashion), on textual aspects of style (rather than production-or reception-oriented theories of style), and on a descriptive perspective (rather than a prescriptive or didactic one). Even within these limits, however, it appears necessary to build on a broad understanding of the various perspectives on style that have been adopted at different times and in different traditions. For this reason, the contribution first traces the development of the notion of style in three different traditions, those of German, Dutch and French language and literary studies. Despite the numerous links between each other, and between each of them to the British and American traditions, these three traditions each have their proper dynamics, especially with regard to the convergence and/or confrontation between mainstream and computational stylistics. For reasons of space and coherence, the contribution is limited to theoretical developments occurring since 1945.The contribution begins by briefly outlining the range of definitions of style that can be encountered across traditions today: style as revealing a higherorder aesthetic value, as the holistic ›gestalt‹ of single texts, as an expression of the individuality of an author, as an artifact presupposing choice among alternatives, as a deviation from a norm or reference, or as any formal property of a text. The contribution then traces the development of definitions of style in each of the three traditions mentioned, with t...

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“…We evaluated these features in a binary classification task using the VU Amsterdam Metaphor Corpus (Steen, et al, 2010), which consists of 200,000 words from the British National Corpus divided into four genres (academic, news, fiction, and spoken; the spoken genre was not evaluated) and annotated by five linguists. Metaphorically used prepositions have been untagged, as have ambiguously metaphoric sentences.…”

Section: Evaluation Of the Featuresmentioning

confidence: 99%

Multi-dimensional abstractness in cross-domain mappings

Dunn¹

2014

Proceedings of the Second Workshop on Metaphor in NLP

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Metaphor is a cognitive process that shapes abstract target concepts by mapping them to concrete source concepts. Thus, many computational approaches to metaphor make reference, directly or indirectly, to the abstractness of words and concepts. The property of abstractness, however, remains theoretically and empirically unexplored. This paper implements a multi-dimensional definition of abstractness and tests the usefulness of each dimension for detecting cross-domain mappings.

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Metaphor in usage

Cited by 164 publications

References 13 publications

Measuring metaphoricity

Measuring metaphoricity

Revisiting Style, a Key Concept in Literary Studies

Multi-dimensional abstractness in cross-domain mappings

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