Colin Fay is a data scientist, R consultant, and trainer with a decade of experience helping teams build robust data products and Shiny apps from Brittany, France. As a core contributor at ThinkR he combines R engineering, full-stack Shiny development, and training, and has improved flagship projects like shiny and the golem framework. His open-source work includes internationalizing tidytext tokenization for multiple languages and adding advanced n-gram methods, reflecting a practical focus on multilingual text mining and tooling. Co-founder of the Breizh Data Club and creator of Data Bzh, he pairs community-driven open data projects with hands-on engineering. Off-duty he’s a runner and plant-based eater—bringing the same disciplined curiosity to code and community.
9 years of coding experience
2 years of employment as a software developer
Master's degree, English Language and Literature/Letters, Mention Bien (15,5), Master's degree, English Language and Literature/Letters, Mention Bien (15,5) at Université Rennes II - Haute-Bretagne
Contributions:13 releases, 31 reviews, 996 commits in 4 years 7 months
Contributions summary:Colin focused on the initial setup and development of a Shiny application framework, as evidenced by their contributions to create a project template. Their work included defining dependencies, setting up test infrastructure, and establishing the core file structure. They also implemented user interface design, and server-side logic and code documentation.
Text mining using tidy tools :sparkles::page_facing_up::sparkles:
Role in this project:
Back-end Developer
Contributions:25 commits, 13 PRs, 14 comments in 2 years
Contributions summary:Colin primarily contributed to expanding the `tidytext` library's internationalization capabilities. Their commits focused on adding support for multiple languages (French, German, Italian, and Spanish) by integrating with the `hunspell` library for tokenization. They modified core functions like `unnest_tokens` and created specialized tokenization functions to handle foreign languages, and also implemented tests to validate the new language support. The user also introduced functionality for unnesting n-grams, skip-ngrams, and other tokenization methods.
pythonminingtidytext-miningsparkles
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