- Recommended web browsers: Firefox or Chrome; Safari and Edge should also work for most tasks, but have not been fully tested.
- Create a ctext account and log in
- Check your e-mail (and spam folder) for an e-mail sent from the system, and click the link in the e-mail to validate your account.
- Go to “Settings” at the bottom left, enter the API key specified in the live session in the box under “API key”, and click “Save”
- Install the Text Tools plugin by opening this link, and then clicking “Install”
- Install the Annotation plugin by opening this link, and then clicking “Install”
Some parts of the material that will be covered in the session are available in step-by-step tutorials, which also include other details and examples and might be useful if you want to come back to the material later:
- Practical introduction to ctext.org – interactive guide to core functionality of the Chinese Text Project.
- Text Tools for ctext.org – interactive guide to using the Text Tools plugin for the Chinese Text Project for text mining and data visualization.
- ctext.org Data Wiki tutorial – interactive guide to working with the Data wiki
- the posts on text reuse and regular expressions on Digital Sinology.
For those interested in using ctext with Python (or another programming language), see also:
- Classical Chinese Digital Humanities (on Digital Sinology) – step-by-step guide to getting started with programming in Python, and accessing the CTP API for simple text mining.
- “ctext” Python module and CTP API documentation
- Some [very] brief notes on using a ctext data wiki RDF dump in Python
These parts of the ctext.org instructions should also be useful:
Lastly, some of these papers may be of interest:
- Digitizing Premodern Text with the Chinese Text Project, Journal of Chinese History 2020, 4(2).
- Chinese Text Project: a dynamic digital library of premodern Chinese, Digital Scholarship in the Humanities (2019)
- Digital Approaches to Text Reuse in the Early Chinese Corpus, Journal of Chinese Literature and Culture 2018, 5(2).
- Large-scale Optical Character Recognition of Pre-modern Chinese Texts, International Journal of Buddhist Thought and Culture 2018, 28(2).
- Unsupervised Identification of Text Reuse in Early Chinese Literature, Digital Scholarship in the Humanities (2018)
Local (non-ctext) annotation example
Download and save the file: qidan-guozhi1.xml (契丹國志卷一). You can load this into the Annotation client without using the ctext.org API.
Using materials not in classical Chinese
If we have time, we’ll quickly look at how this works in Text Tools. For simplicity, here are links to two very simple sets of example data: