Keywords
Controversy analysis
Artificial intelligence
Hamas-Israel conflict
Science and Technology Studies (STS)
How to Cite
Abstract
This article offers a critical reflection on the use of the BERT model as a tool to classify stances in public controversies, focusing on the case of the Hamas-Israel conflict. Based on a corpus of over 250,000 Spanish-language YouTube comments (October 2023–January 2024), BERT was trained using a manually annotated sample to identify seven discursive categories. Although the model achieved an accuracy of 92.76%, it failed to correctly classify the Anti-Hamas category, revealing its limitations and biases. The article argues that BERT functions not only as a classifier but also as an inscription device that simplifies complex social phenomena. By combining artificial intelligence with controversy analysis and Science and Technology Studies (STS), it is suggested that language models do not merely detect patterns but actively co-construct meaning. The article concludes that the use of such models must be critically examined through ethical, theoretical, and epistemic frameworks.
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