The best way to learn about snelSLiM? Go to demo

Try it out yourself at using a few publicly available corpora.

Want to learn more or get a detailed explanation? Have a look at the user manual, where you can see the rational between certain functionality and find more information about features that are disabled on the demo.

Looking for more general information?

In the next few days the main website will be launched, including some YouTube videos to help those interested to understand what the tool is capable of and how to use it.

Technical information

If you wish to install snelSLiM or learn more about technical aspects such as the supported corpus formats, you can view the technical side of things on GitHub and depending on your interest the installation manual.

References for snelSLiM

Bert Van de Poel and Dirk Speelman. SnelSLiM, a user-friendly and fast tool to perform better keyword analysis through Stable Lexical Marker Analysis. Computational Linguistics in the Netherlands Journal, 10:147--160, December 2020. [ bib | http ]

Bert Van de Poel. snelSLiM [software], 2021. Available at: [ bib ]

References for Stable Lexical Marker Analysis

Dirk Speelman, Stefan Grondelaers, and Dirk Geeraerts. Variation in the choice of adjectives in the two main national varieties of dutch. In Gitte Kristiansen and René Dirven, editors, Cognitive Sociolinguistics: Language Variation, Cultural Models, Social Systems, volume 39, pages 205--233. Walter de Gruyter, 2008. [ bib ]

Dirk De Hertog, Kris Heylen, and Dirk Speelman. The prevalence of multiword term candidates in a legal corpus. In Proceedings of the 10th Terminology and Knowledge Engineering Conference (TKE2012): New frontiers in the constructive symbiosis of terminology and knowledge engineering, pages 283--290. Universidad Politecnica de Madrid, 2012. [ bib ]

Dirk De Hertog, Kris Heylen, and Dirk Speelman. Stable lexical marker analysis: a corpus-based identification of lexical variation. In Augusto Soares Da Silva, editor, Pluricentricity: Language variation and sociocognitive dimensions, volume 24, pages 127--141. Walter de Gruyter, 2014. [ bib ]