We've got a new article out
*Angst M, Müller NN, Walker V. Automated extraction of discourse networks from large volumes of media data* (open access)
https://doi.org/10.1017/nws.2025.4
As part of our sustainability.discourses project, we developed an automated method to gather and track discourse networks around urban sustainable mobility, based on media data.
The article describes the approach in detail and reports an evaluation of the internal validity (do we measure what we ourselves think we measure) of the pipeline.
tl;dnr: Automating discourse network data gathering can work well to capture broader tendencies. In many cases, it is likely not worth investing in automating data gathering to understand discourse however.
Want to see the daily updated pipeline in action? Check out the web apps and resources here: https://sustainability.discourses.ch/en/
Implications for Data Privacy: Our findings have real-world relevance for data owners worried about unauthorized use of their content in model training. It can also be used to support accountability of LLM evaluation in end-tasks. 
What Do You Think? Could MIA reach a level where data owners use it as legal evidence? How might this affect LLM deployment? Let us know! 
CFP Link: 
Paper Submission DL: May 18