Cover not available

Article published In: International Journal of Corpus Linguistics
Vol. 24:2 (2019) ► pp.245–261

Get fulltext from our e-platform
JBE logo with link
PDF logo with download linkDownload PDF
authorization required

Kaleidographic

A data visualization tool

 | University of New South Wales
 | Waseda University
 | The University of Sydney | Freiburg Institute for Advanced Studies
Published online: 5 August 2019
DOI logo with link
https://doi.org/10.1075/ijcl.18038.cap
Abstract
Kaleidographic is a dynamic and interactive data visualization tool that allows users to observe and explore relations between any number of variables. The tool is useful for displaying the complex ways in which textual elements interact across a range of texts. Thus far, the tool has been used to display the results of corpus studies as well as corpus-assisted multimodal discourse analyses that investigate text-image relations. To facilitate broader applications of the tool, it is now publicly available online for use without charge. This paper explains the background and motivation for Kaleidographic and presents two case studies demonstrating its utility. Limitations of the tool are discussed and its potential uses in corpus linguistics research and beyond are introduced.
Article outline
  • 1.Introduction
  • 2.What is data visualization?
  • 3.What is Kaleidographic?
    • 3.1Features of Kaleidographic
      • 3.1.1Basic view and controls
      • 3.1.2Filters
      • 3.1.3Speed
      • 3.1.4Aggregation of results
    • 3.2 Kaleidographic builder
    • 3.3Sharing visualizations
  • 4.How has Kaleidographic been used?
    • 4.1Case Study 1: Swear/taboo words in US TV series
    • 4.2Case Study 2: Instagram
  • 5.Conclusions
  • Acknowledgements
  • Note
  • References
References (19)
References
Allen, W. (2017). Making corpus data visible: Visualising text with research intermediaries. Corpora, 12 (3), 459–482. Google Scholar logo with link to Google Scholar
Anthony, L. (2018). Visualisation in corpus-based discourse studies. In C. Taylor & A. Marchi (Eds.), Corpus Approaches to Discourse: A Critical Review (pp. 197–224). London/New York, NY: Routledge. Google Scholar logo with link to Google Scholar
Bednarek, M. (2018). Methodology notes: Analysis of eight swear/taboo word forms in SydTV-Std. Retrieved from: [URL] (last accessed April 2019).
Bednarek, M., & Caple, H. (2014). Why do news values matter? Towards a new methodological framework for analyzing news discourse in Critical Discourse Analysis and beyond. Discourse & Society, 25 (2), 135–158. Google Scholar logo with link to Google Scholar
(2017). The Discourse of News Values: How News Organizations Create Newsworthiness. New York, NY: Oxford University Press. Google Scholar logo with link to Google Scholar
Brezina, V., McEnery, T., & Wattam, S. (2015). Collocations in context. International Journal of Corpus Linguistics, 20 (2), 139–73. Google Scholar logo with link to Google Scholar
Caple, H. (2018). Analysing the multimodal text. In C. Taylor & A. Marchi (Eds.), Corpus Approaches to Discourse: A Critical Review (pp. 85–109). London/New York, NY: Routledge. Google Scholar logo with link to Google Scholar
Caple, H., & Bednarek, M. (2017). Kaleidographic [Computer Software]. Retrieved from: [URL] (last accessed April 2019).
Card, S. K., Mackinlay, J. D., & Shneiderman, B. (Eds.) (1999). Readings in Information Visualization: Using Vision to Think. San Francisco, CA: Morgan Kaufmann.Google Scholar logo with link to Google Scholar
Dörk, M., & Knight, D. (2015). WordWanderer: A navigational approach to text visualisation. Corpora, 10 (1), 83–94. Google Scholar logo with link to Google Scholar
Engebretsen, M., & Weber, W. (2017). Graphic modes: The visual representation of data. In D. Perrin & C. Cotter (Eds.), Handbook of Language and Media (pp. 277–295). London: Routledge.Google Scholar logo with link to Google Scholar
Graham, E. (2017). Introduction: Data visualisation and the Humanities. English Studies, 98 (5), 449–458. Google Scholar logo with link to Google Scholar
Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design. London: SAGE.Google Scholar logo with link to Google Scholar
Lima, M. (2011). Visual Complexity: Mapping Patterns of Information. New York, NY: Princeton Architectural Press.Google Scholar logo with link to Google Scholar
Rayson, P. E., Mariani, J. A., Anderson-Cooper, B., Baron, A., Gullick, D. S., Moore, A., & Wattam, S. (2017). Towards interactive multidimensional visualisations for corpus linguistics. Journal for Language Technology and Computational Linguistics, 31 (1), 27–49.Google Scholar logo with link to Google Scholar
Scott, M. (2012). WordSmith Tools (Version 6) [Computer software]. Stroud: Lexical Analysis Software.Google Scholar logo with link to Google Scholar
Sinclair, S., Rockwell, G., & the Voyant Tools Team (2012). Voyant Tools [Web application]. Retrieved from [URL] (last accessed April 2019).
Spinillo, C. G. (2017). Introduction: Information visualization, a design challenge. Information Design Journal, 23 (1), 1–2. Google Scholar logo with link to Google Scholar
Zappavigna, M. (2011). Visualizing logogenesis: Preserving the dynamics of meaning. In S. Dreyfus, S. Hood & M. Stenglin (Eds.), Semiotic Margins: Meaning in Multimodalities (pp. 211–228). London/New York, NY: Continuum.Google Scholar logo with link to Google Scholar
Cited by (1)

Cited by one other publication

Isaacs, Loryn, Alex Odlum & Pilar León-Araúz
2024. Quartz: A Template for Quantitative Corpus Data Visualization Tools. Languages 9:3 ► pp. 81 ff. DOI logo

This list is based on CrossRef data as of 12 december 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

Mobile Menu Logo with link to supplementary files background Layer 1 prag Twitter_Logo_Blue