-
Notifications
You must be signed in to change notification settings - Fork 2
9 Visualisation
Thursday Dec 3, 16:00 UK = 17:00 CET
Convenors: Aurélien Berra (Paris Nanterre), Gabriel Bodard (University of London), Naomi Wells (University of London)
YouTube link: https://youtu.be/1nDK1DqMp_g
Slides: tba
This session will follow up on the approaches discussed in previous sessions on computational lingustics and using treebanks to present a third digitally assisted or “distant reading” method to text analysis. We will begin with an introduction to the Voyant Tools suite, and a discussion and demonstration of its use for analysing texts and corpora visually. We will then move to a discussion of visualisations of text and data more generally, including research and communication issues, and round off with a discussion of a few interesting examples of visualisations.
For [discussion in this forum thread]
- Drucker, Johanna, “Humanities Approaches to Graphical Display”, Digital Humanities Quarterly 5.1, 2011, http://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html.
- Glinka K., Pietsch C. and Dörk M., “Past Visions and Reconciling Views: Visualizing Time, Texture and Themes in Cultural Collections”, Digital Humanities Quarterly 11, 2017. Available: http://digitalhumanities.org/dhq/vol/11/2/000290/000290.html.
- Hawkins, Laura F., “Computational Models for Analyzing Data Collected from Reconstructed Cuneiform Syllabaries”, Digital Humanities Quarterly 12.1, 2018, http://digitalhumanities.org:8081/dhq/vol/12/1/000368/000368.html.
- Rockwell, Geoffrey and Sinclair, Stéfan, “The Swallow Flies Swiftly Through: An Analysis of Humanist”, in Hermeneutica. Computer-Assisted Interpretation in the Humanities, Cambridge, Massachusetts, MIT Press, 2016, http://hermeneuti.ca/swallow-flies.
- Friendly, Michael, “A Brief History of Data Visualization”, in Handbook of Computational Statistics: Data Visualization, Springer Verlag, 2006, 15-56. Available: http://www.datavis.ca/papers/hbook.pdf.
- Risam, R. (2019). “Beyond the Migrant ‘Problem’: Visualizing Global Migration.” Television & New Media 20(6), 566–580. (abstract)
- Rockwell, Geoffrey, “What is Text Analysis, Really?”, Literary and Linguistic Computing 18.2, 2003, 209-219. Available: http://www.geoffreyrockwell.com/publications/WhatIsTAnalysis.pdf.
- Schöch, Christof, “Big? Smart? Clean? Messy? Data in the Humanities”, Journal of Digital Humanities 2.3, 2013, http://journalofdigitalhumanities.org/2-3/big-smart-clean-messy-data-in-the-humanities/.
- Tufte, Edward R., The Visual Display of Quantitative Information, Cheshire, Connecticut, Graphic Press, 2nd ed., 2001.
- Sinclair, Stéfan and Rockwell, Geoffrey, Voyant Tools, 2016, http://voyant-tools.org/. Tutorial: https://voyant-tools.org/docs/#!/guide/tutorial.
- Data visualisation galleries
- Holtz, Yan and Healy, Conor, From Data to Viz, https://www.data-to-viz.com, 2018.
- Holtz, Yan, The R Graph Gallery, http://r-graph-gallery.com, 2018.
- Holtz, Yan, The Python Graph Gallery, https://python-graph-gallery.com, 2017.
- Kucher, Kostiantyn and Kerren, Andreas, Text Visualization Browser, https://textvis.lnu.se/, 2015.
- Healy, Kieran, Data Visualization: A Practical Introduction, Princeton, Princeton University Press, 2019, https://press.princeton.edu/books/hardcover/9780691181615/data-visualization – online draft, 2018, http://socviz.co/.
- Wilke, Claus O., Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures, Sebastopol, CA, O’Reilly Media, 2019. Website version, 2019, https://serialmentor.com/dataviz/ – see especially chap. 5, “Directory of visualizations”, https://serialmentor.com/dataviz/directory-of-visualizations.html.
- Seeing Data. Developing Visualisation Literacy, 2016, http://seeingdata.org/.
- Dombrowski, Q., 2020. Preparing Non-English Texts for Computational Analysis. Modern Languages Open, (1), p.45. DOI: http://doi.org/10.3828/mlo.v0i0.294.
-
Select an Ancient Greek or Latin (or translated) text to analyse and import it into Voyant Tools
-
Explore several types of visualisation, and test the effect of applying a stopword list to understand the interest of this typical pre-processing step (Voyant provides customisable lists for several languages)
- Visualise and reflect: What do you observe? Which types of visualisation were most useful to get insights into this corpus, and why? Which visualisation seemed most obscure or least useful?
-
Do the same analysis again on a lemmatised text (if you have used one of the texts suggested below, we also provide lemmatised versions): What is the impact of such linguistic pre-processing on the visualisations produced by Voyant?
-
Suggested texts (if you have no preferences):
- Iliad: Monro-Allen 1920 edition in Perseus (XML); Lemmatised version of this edition (TXT)
- Odyssey: Murray 1919 edition in Perseus (TXT) and compressed file with separate files for the books (ZIP, can be loaded into Voyant to get one “document” per book); Lemmatised version of Murray edition in Perseus (TXT); lemmatised files for the same edition (ZIP)
- Sallust: Ahlberg 1919 edition (TXT); Lemmatised version of Ahlberg edition (TXT)
- Use one or more of the following tutorials to familiarise yourself with either Tableau Public or RawGraphs:
- Choose one of the datasets provided (or – advanced – another dataset you are familiar with), and familiarise yourself with the data (e.g. open the CSV in Excel, Numbers or GoogleSheets):
- Roman Amphitheaters
- Early Women Graduates
- Roman Mithraea (incomplete)
- London street trees (sample)
- Open the dataset in Tableau/RAWgraphs
- Discuss and share with your group practice visualisations or questions about the dataset
- Particularly in Tableau, there are many different ways to export or share your visualisations (e.g. you may want to experiment with creating a public dashboard) but for the purposes of this exercise, it will be easiest to post your image/vector files to the discussion forum to share with the larger group
[If you have any technical problems with this exercise, you may ask for help in this forum thread.]