Welcome! forager is a Python-based web interface to analyze verbal fluency task (VFT) data.

You can use forager to obtain cluster-switch designations based on a variety of methods, run computational models of search (based on optimal foraging), and also obtain estimates of semantic similarity, phonological similarity, and frequency for items produced by participants.

To know more about forager, explore the tabs on the sidebar, such as our docs or about page.

what would you like forager to do?

Hover over the buttons to learn more about each option.

Upload your data

Upload data as a tab-delimited .txt or CSV file, with column headers for subject ID and words. Please review the docs page to understand the file formats forager accepts.

Please note: If your data has 3 columns, forager will automatically treat the third column as a timepoint. If you do not want this, please remove the third column before uploading.

Please select how you would like forager to handle words that are out of the vocabulary set (OOV) and do not have any reasonable replacements. We recommend excluding them from the analysis.

Evaluation results:

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If you would like to proceed with the corrected data, please click the button below. Otherwise, please upload a new file and re-run the evaluation by clicking on 'Check Data' again.

NOTE: If you decide to upload a new file, please make sure to reload the page before uploading to clear the data from the previous run.

This interface currently supports obtaining similarity and cluster-switch values. To run foraging models, please use the Colab notebook to which you have been redirected.

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If you use forager, please use the guidelines on the cite page to cite our work!