Today, Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) discuss together with Valerie Hase (Research and Teaching Assistant at the U of Zurich) ways, approaches, guidelines, and routes to get started with computational communication science (CCS). We talk learning materials, compare intrinsic and extrinsic motivation, provide ideas and suggestions on where and how to find help and companions, and we tell our very own stories of how we got started with CCS.
Conferences, Divisions, & Working Groups
https://www.icahdq.org/group/compmethds
- Slack channel via https://twitter.com/fe_loe/status/1395020548019720193
https://www.dgpuk.de/de/methoden-der-publizistik-und-kommunikationswissenschaft.html
- https://twitter.com/dgpuk_meth
https://www.cssmethods.uzh.ch/en.html
https://cssamsterdam.github.io/
Journals
https://computationalcommunication.org/ccr
https://www.tandfonline.com/toc/hcms20/current
References
van Atteveldt, W., Trilling, D., & Arcila Calderon, C. (2021). Computational analysis of communication. Wiley Blackwell. https://cssbook.net/
Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, tidy, transform, visualize, and model data. O'Reilly.
Summer Schools
https://github.com/chkla/css-schools
https://essexsummerschool.com/
https://wiki.digitalmethods.net/Dmi/DmiAbout
Introductory Tutorials
https://www.tidytextmining.com/
https://tutorials.quanteda.io/
https://content-analysis-with-r.com/
https://bookdown.org/joone/ComputationalMethods/
https://www.mzes.uni-mannheim.de/socialsciencedatalab/article/advancing-text-mining/
