Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,66 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Dataset Card: Multi-Task German Text Classification Dataset
|
| 2 |
+
|
| 3 |
+
## Dataset Description
|
| 4 |
+
|
| 5 |
+
This dataset contains German text samples labeled for three tasks:
|
| 6 |
+
1. **Fake News Detection (`is_fake`)**
|
| 7 |
+
2. **Hate Speech Detection (`is_hate_speech`)**
|
| 8 |
+
3. **Toxicity Detection (`is_toxic`)**
|
| 9 |
+
|
| 10 |
+
Each entry in the dataset has binary or missing labels for the respective tasks:
|
| 11 |
+
- `0`: Negative
|
| 12 |
+
- `1`: Positive
|
| 13 |
+
- `-1`: Not labeled for the task
|
| 14 |
+
|
| 15 |
+
The dataset is useful for training and evaluating models on multi-task learning objectives in the context of online German text.
|
| 16 |
+
|
| 17 |
+
---
|
| 18 |
+
|
| 19 |
+
## Dataset Structure
|
| 20 |
+
|
| 21 |
+
| **Column** | **Description** |
|
| 22 |
+
|-----------------------|-----------------------------------------------------------|
|
| 23 |
+
| `text` | The German text sample |
|
| 24 |
+
| `is_fake` | Binary label for fake news detection (0 or 1) |
|
| 25 |
+
| `is_hate_speech` | Binary label for hate speech detection (0, 1, or -1) |
|
| 26 |
+
| `is_toxic` | Binary label for toxicity detection (0, 1, or -1) |
|
| 27 |
+
|
| 28 |
+
### Sample Data
|
| 29 |
+
|
| 30 |
+
| **Text** | `is_fake` | `is_hate_speech` | `is_toxic` |
|
| 31 |
+
|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------|------------------|------------|
|
| 32 |
+
| Im Studio von @1730Sat1live sprechen wir heute mit Stefan Schulte, dem Vorstandsvorsitzenden der @FraportAG, über die Lage am Frankfurter Flughafen... | 0 | -1 | -1 |
|
| 33 |
+
| gigi hat einfach überhaupt keine lust mehr auf lucas. gigi 🤝 wir alle #ibes | 0 | -1 | -1 |
|
| 34 |
+
| In Österreich 🇦🇹 ist Bundespräsident @vanderbellen für eine 2. Amtszeit angelobt worden... | 0 | -1 | -1 |
|
| 35 |
+
| Was ist der Mindestlohn pro Stunde in Vietnam? https://t.co/VQof8kwRlL | 0 | -1 | -1 |
|
| 36 |
+
| #GretaThunberg will jetzt den #Kapitalismus überwinden... | 0 | -1 | -1 |
|
| 37 |
+
|
| 38 |
+
---
|
| 39 |
+
|
| 40 |
+
## Usage
|
| 41 |
+
|
| 42 |
+
This dataset is designed for training and evaluating multi-task classification models in German. The tasks include:
|
| 43 |
+
- Fake news detection
|
| 44 |
+
- Hate speech identification
|
| 45 |
+
- Toxicity assessment
|
| 46 |
+
|
| 47 |
+
### Example Usage in Python
|
| 48 |
+
|
| 49 |
+
```python
|
| 50 |
+
import pandas as pd
|
| 51 |
+
|
| 52 |
+
# Load the dataset
|
| 53 |
+
df = pd.read_csv("path_to_dataset.csv")
|
| 54 |
+
|
| 55 |
+
# Access text and labels
|
| 56 |
+
for index, row in df.iterrows():
|
| 57 |
+
text = row['text']
|
| 58 |
+
is_fake = row['is_fake']
|
| 59 |
+
is_hate_speech = row['is_hate_speech']
|
| 60 |
+
is_toxic = row['is_toxic']
|
| 61 |
+
|
| 62 |
+
# Example: Print the data
|
| 63 |
+
print(f"Text: {text}, Fake: {is_fake}, Hate Speech: {is_hate_speech}, Toxic: {is_toxic}")
|
| 64 |
+
```
|
| 65 |
+
|
| 66 |
+
|