In this session, we will talk about text mining and digital text. I will show my work in progress, talk about sopme theory and project workflows.
Additionally it might be time to discuss some legal issues, as already mentioned in [this issue](https://gitlab.uzh.ch/lit/digizeit/issues/29).
I already made a small work in progress wiki with some very [general notes](https://gitlab.uzh.ch/lit/digizeit/-/wikis/Information/Digital-Text-for-text-mining). You can have a look at it as well.
## Links
* For the article Martin mentioned in class on 10 March, see: Peter Broadwell et al, [“Reading the *Quan Tang shi*: Literary History, Topic Modeling, Divergence Measures”](http://digitalhumanities.org/dhq/vol/13/4/000434/000434.html), *Digital Humanities Quarterly* 13, 4 (2019)
* There is a book that I find quite helpful since it shows different case studies and approaches to text mining. The contributers all use the same text corpus and the same mining software. The only problem: The book is in [German](https://www.deepl.com/de/translator):
[Text Mining in den Sozialwissenschaften](https://link.springer.com/book/10.1007/978-3-658-07224-7)
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## My project
Plese check out my project's GitLab page [here](https://gitlab.uzh.ch/patrick.gut/blended-readings)!
