---
language: multilingual
license: apache-2.0
tags:
- political-bias
- bias-detection
- news-analysis
- xlm-roberta
pipeline_tag: text-classification
---

# WorldVue Balanced Political Bias Detector

This model detects political bias in news articles across economic and social dimensions.

## Model Description

- **Architecture**: mDeBERTa-v3-base (278M parameters)
- **Training Data**: 6,000 articles judged by GPT-4o-mini
- **Languages**: 100+ (multilingual)
- **Axes**:
  - Economic: LEFT (-1) ← CENTER (0) → RIGHT (+1)
  - Social: LIBERTARIAN (-1) ← CENTER (0) → AUTHORITARIAN (+1)

## Signals Detected

**Economic (4 signals):**
1. Economic Role of State
2. Market & Business
3. Taxation & Spending
4. Labor & Trade

**Social (4 signals):**
1. State Authority vs Liberty
2. Cultural Identity
3. Immigration & Borders
4. Collective vs Individual

## Usage

```python
from transformers import AutoTokenizer, AutoModel
import torch
import torch.nn as nn

# Load model
tokenizer = AutoTokenizer.from_pretrained("Xiameineedsgpu/worldvue-balanced-bias-detector")
# ... (see example code below)
```

## Training Details

- **Test Loss**: 2.13
- **Political Articles**: 3,112
- **Non-Political Articles**: 2,888
- **Training Time**: ~1 hour on Google Colab (T4 GPU)

## Example Outputs

| Article | Economic | Social | Label |
|---------|----------|--------|-------|
| Fox News - Immigration | +0.02 | +0.83 | CENTER / AUTHORITARIAN |
| Energy Transition | -0.24 | -0.23 | LEFT / LIBERTARIAN |
| UK PPE Scandal | +0.10 | +0.25 | RIGHT / AUTHORITARIAN |

## License

Apache 2.0