Chaima-KHENAFIF/fake-news-spreader-detector
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Fake News Spreader Detector
A fine-tuned bert-base-uncased model that classifies a Twitter user as a fake news spreader or not, based on their aggregated post history.
Trained on a PAN-format author profiling dataset. TF-IDF + classical models (Logistic Regression, SVM, Random Forest, Naive Bayes) were compared as baselines before fine-tuning BERT as the final approach.
Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="Chaima-KHENAFIF/fake-news-spreader-detector")
classifier("aggregated user post text goes here")Training
Fine-tuned for up to 5 epochs with early stopping (patience 1, selected on F1), on text cleaned via lemmatization, stopword/punctuation/URL/mention removal.
Results
Links
- Full code, training pipeline, and Flask interface: GitHub repo