What is ActiveTigger?
ActiveTigger1 is an open-source software designed to support collaborative text annotation for computational social sciences. It is designed to assist exploration and model fine-tuning (BERT) to annotate text datasets relying on active learning.
ActiveTigger could help you if you…
- want to classify large datasets of texts (social media posts, news articles...)
- are working collaboratively with other human annotators
- want to get an overview of key topics in your text data
- are curious about supervised machine learning for text and want an easy introduction
How to start?
- Take a look at our Quickstart guide
- Watch one of our live introduction sessions
- Try it yourself!
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The current version is a refactor of R Shiny ActiveTigger app (Julien Boelaert & Etienne Ollion). ActiveTigger name is a pun that draws on the similarity between the words 'Tagger' and 'Tigger', and the possibility to use active learning (and yes, we're aware that good jokes shouldn't need a footnote). ↩