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CQPweb — combining power, flexibility and usability in a corpus analysis tool
Abstract
CQPweb is a new web-based corpus analysis system, intended to address the conflicting requirements for usability and power in corpus analysis software. To do this, its user interface emulates the BNCweb system. Like BNCweb, CQPweb is built on two separate query technologies: the IMS Open Corpus Workbench and the MySQL relational database. CQPweb’s main innovative feature is its flexibility; its more generalised data model makes it compatible with any corpus. The analysis options available in CQPweb include: concordancing; collocations; distribution tables and charts; frequency lists; and keywords or key tags. An evaluation of CQPweb against criteria earlier laid down for a future web-based corpus analysis tool suggests that it fulfils many, but not all, of the requirements foreseen for such a piece of software. Despite some limitations, in making a sophisticated query system accessible to untrained users, CQPweb combines ease of use, power and flexibility to a very high degree.
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Cited by
Kilgarriff, A., Baisa, V., Bušta, J., Jakubíček, M., Kovář, V., Michelfeit, J., Rychlý, P., & Suchomel, V. (2014) · Lexicography · doi:10.1007/s40607-014-0009-9 · Cited by 2,105
Corpus-Assisted Discourse Studies
Gillings, M., Mautner, G., & Baker, P. (2023) · doi:10.1017/9781009168144 · Cited by 146
Millar, N., Batalo, B., & Budgell, B. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.28676 · Cited by 57
Swearing in informal spoken English: 1990s–2010s
Love, R. (2021) · Text & Talk · doi:10.1515/text-2020-0051 · Cited by 40
Metadata
- Authors
- Hardie, A.
- Venue
- International Journal of Corpus Linguistics
- Publisher
- John Benjamins Publishing Company
- Published
- 2012-12-31
- Volume
- 17
- Issue
- 3
- Pages
- 380-409
- ISSN
- 1384-6655 (ISSN-L)
- 1569-9811
- OpenAlex
- W2095503871
- Cited by
- 515
- References
- 0
- FWCI
- 13.93
- Type
- journal article
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.