Introduction
The ILLFRAMES Babel Machine uses the ILLFRAMES policy frames codebook to identify illiberal policy frames in texts. The codes are mutually exclusive and unequivocal. The codebook currently only covers the policy domain of migration and covid, but other policy domains such as climate, public health, and democracy will be added in the near future.
The model was the trained on sentence-level English language data and currently supports only datasets in English.
You can upload your datasets here for automated illiberal frames coding. If you wish to submit multiple datasets one after another, please wait 5-10 minutes between each of your submissions.
The upload requires you to fill the following form on metadata regarding the dataset. Please upload non-coded datasets, which should contain an id and a text column. The column names must be in row 1. You are free to add supplementary variables to the dataset beyond the compulsory ones in the columns following them.
After you upload your dataset and your file is successfully processed, you will receive the illiberal policy frames-coded dataset and a file (in CSV format) that includes the predictions by our model.
If the files you would like to upload are larger than 1 GB, please reach out to us with the download link attached (such as Dropbox or Google Drive) using our contact form.
If you have any questions or feedback regarding the Babel Machine, please let us know using our contact form. Please keep in mind that we can only get back to you on Hungarian business days.
Submit a dataset:






The research was supported by the Ministry of Innovation and Technology NRDI Office within the RRF-2.3.1-21-2022-00004 Artificial Intelligence National Laboratory project and received additional funding from the European Union's Horizon 2020 program under grant agreement no 101008468. We also thank the Babel Machine project and HUN-REN Cloud (Héder et al. 2022; https://science-cloud.hu) for their support. We used the machine learning service of the Slices RI infrastructure (https://www.slices-ri.eu/)
HOW TO CITE: If you use the Babel Machine for your work or research, please cite this paper:
Sebők, M., Máté, Á., Ring, O., Kovács, V., & Lehoczki, R. (2024). Leveraging Open Large Language Models for Multilingual Policy Topic Classification:
The Babel Machine Approach. Social Science Computer Review, 0(0). https://doi.org/10.1177/08944393241259434
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