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fake-news-spreader-detector
Chaima-KHENAFIF/fake-news-spreader-detector
fake-news-spreader-detector is a text classification model from Chaima-KHENAFIF. Use it when you need a label for a piece of text. The card lists the license as mit.
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.
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At a glance
- Task
- Text Classification
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Aug 26, 2026
- Updated
- Aug 27, 2026
- SHA
- 7e517da6
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Base models
Model card
From the Hugging Face model README
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
| Metric | Score |
|---|---|
| Accuracy | TODO |
| F1 | TODO |
Links
- Full code, training pipeline, and Flask interface: GitHub repo
- Task
- Text Classification
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Aug 26, 2026
- Updated
- Aug 27, 2026