Perspectives on keywords and keyness

Bondi, Marina

doi:10.1075/scl.41.01bon

Cited by 50 publications

(30 citation statements)

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Section: Data and Proceduresmentioning

confidence: 99%

“…As Bondi () rightly points out, keywords, like most frequency data, only point at elements that may be of interest. A more important task of keyword analysis is to provide an explanation, which ‘is likely to be found in the co‐text of the items, and ultimately in the text’ (Bondi, , p.14). In the present study, the concordancing function in WordSmith tools was used to display the concordances of the keywords, which were then checked to identify the main function(s) and collocational pattern(s) of a given keyword.…”

Section: Data and Proceduresmentioning

confidence: 99%

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Linguistic differences between well‐established and predatory journals: a keyword analysis of two journals in political science

Soler

Wang

2019

Learned Publishing

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Predatory publishing has become a much‐discussed and highly visible phenomenon over the past few years. One widespread, but hardly tested, assumption is the idea that articles published in predatory journals deviate substantially from those published in traditional journals. In this paper, we address this assumption by utilizing corpus linguistic tools. We compare the ‘academic‐like’ nature of articles from two different journals in political science, one top‐ranking and one alleged predatory. Our findings indicate that there is significant linguistic variation between the two corpora along the dimensions that we test. The articles display notable differences in the types and usage of keywords in the two journals. We conclude that articles published in so‐called predatory journals do not conform to linguistic norms used in higher‐quality journals. These findings may demonstrate a lack of quality control in predatory journals but may also indicate a lack of awareness and use of such linguistic norms by their authors. We also suggest that there is a need for the education of authors in science writing as this may enable them to publish in higher‐ranked and quality‐assured outlets.

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Section: Data and Proceduresmentioning

confidence: 99%

Section: Data and Proceduresmentioning

confidence: 99%

Linguistic differences between well‐established and predatory journals: a keyword analysis of two journals in political science

Soler

Wang

2019

Learned Publishing

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“…For example, Phillips (1989 , p. 51) states that the collocation between electric and charge is also linked to the patterns in the text between their collocations (e.g., charge collocates with distribution , density , point , and uniform ; electric collocates with dipole ). Bondi (2010 , p. 4) affirms that this network of semantic relations identifies the ‘aboutness’ of a text, and is a marker of text content.…”

Section: Context Parametersmentioning

confidence: 86%

Specialized Knowledge Representation and the Parameterization of Context

Faber

León-Araúz

2016

Front. Psychol.

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Though instrumental in numerous disciplines, context has no universally accepted definition. In specialized knowledge resources it is timely and necessary to parameterize context with a view to more effectively facilitating knowledge representation, understanding, and acquisition, the main aims of terminological knowledge bases. This entails distinguishing different types of context as well as how they interact with each other. This is not a simple objective to achieve despite the fact that specialized discourse does not have as many contextual variables as those in general language (i.e., figurative meaning, irony, etc.). Even in specialized text, context is an extremely complex concept. In fact, contextual information can be specified in terms of scope or according to the type of information conveyed. It can be a textual excerpt or a whole document; a pragmatic convention or a whole culture; a concrete situation or a prototypical scenario. Although these versions of context are useful for the users of terminological resources, such resources rarely support context modeling. In this paper, we propose a taxonomy of context primarily based on scope (local and global) and further divided into syntactic, semantic, and pragmatic facets. These facets cover the specification of different types of terminological information, such as predicate-argument structure, collocations, semantic relations, term variants, grammatical and lexical cohesion, communicative situations, subject fields, and cultures.

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“…Some studies have dealt with the linguistic and discursive aspects of the widely read masterworks: Adam Smith's The Wealth of Nations (Bazerman, 1993;Henderson, 2006), Marshall's Elements of Economics (Del Lungo Camiciotti, 2005), and Keynes' General Theory (Bondi, 2010). Other studies have instead focused on the distinctive characteristics of key written economics genres used for the transmission and dissemination of knowledge: prediction in schematic structure in research articles (Dudley-Evans & Henderson, 1990), and economic metaphor in media articles or textbooks (Alejo, 2010;Boers, 2000;Charteris-Black, 2000;Henderson, 1982Henderson, , 1994Henderson, , 2000Hu, 2014;Sun & Jiang, 2014;White, 2003).…”

Section: Introductionmentioning

confidence: 99%

“…Keyword analysis and its extension (key cluster analysis) have been used in numerous studies and applied to a wide variety of research questions ranging from language education (Scott & Tribble, 2006) to sociolinguistics (Baker, 2010), economics (Bondi, 2010), and to literary stylistics (Mahlberg, 2013), to name only a few. While this line of research as practiced by Scott and many followers has exerted immense influence, it is not without its problems.…”

Section: Introductionmentioning

confidence: 99%

Using Wmatrix to Explore Discourse of Economic Growth

Hu¹

2015

ELT

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Growth is a concept of particular interest for economic discourse. This paper sets out to explore a small corpus of economic growth, which consists of articles from The Economist. The corpus software used in this study is a web-based tool Wmatrix, an automatic tagging software able to assign semantic field (domain) tags, and to permit the extraction of key words and key semantic domains by applying the keyness calculation to tag frequency lists. The results show that at 99% confidence (or p < 0.01), the cut-off of 6.63 (log likelihood value) indicates that there are 1051 positive keywords (including multiword expressions) and 80 key semantic domains generated from the corpus. It is evident that BRICs or the emerging economies/markets, in particular China and India, are a big concern regarding economic growth over the past years. A number of examples of possible ways forward in teaching methodology are presented.

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Perspectives on keywords and keyness

Cited by 50 publications

References 0 publications

Linguistic differences between well‐established and predatory journals: a keyword analysis of two journals in political science

Linguistic differences between well‐established and predatory journals: a keyword analysis of two journals in political science

Specialized Knowledge Representation and the Parameterization of Context

Using Wmatrix to Explore Discourse of Economic Growth

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