---
license: apache-2.0
task_categories:
- video-classification
- zero-shot-classification
language:
- en
tags:
- social-signals
- behavioral-analysis
- multimodal
- video
pretty_name: Wave1 Test Set - Social Signal Detection
size_categories:
- n<1K
---

# Wave1 Test Set - Social Signal Detection

## Dataset Description

This dataset contains video clips annotated with social and affective signals for behavioral analysis tasks. Each sample includes:

- **System Prompt**: Instructions for behavioral analysis
- **Video URL**: Link to the video clip
- **Multi-labels**: Detected social signals from 12 categories
- **Video ID**: Unique identifier for the video

## Social Signal Categories

The dataset includes annotations for 12 social signals:

1. **Agreement**: Nods, verbal affirmations, affiliative smiles, posture mirroring
2. **Disagreement**: Opposition, interruptions, head shakes, eye rolls
3. **Engagement**: Sustained orientation, eye contact, forward-leaning posture
4. **Disengagement**: Gaze aversion, fidgeting, low-energy speech
5. **Confusion**: Puzzled facial display, increased blinking, clarification questions
6. **Hesitation**: Long gaps before speaking, filled pauses, restarts
7. **Uncertainty**: Hedged answers, rising final contour, shoulder shrugs
8. **Skepticism**: Questioning stance, delayed responses, furrowed brows
9. **Confidence**: Upright posture, sustained eye contact, clear speech
10. **Frustration**: Tension cues, higher pitch, sighs, complaints
11. **Interest**: Attentional engagement, widened eyes, faster speech
12. **Stress**: Self-touch, repetitive fidgeting, rapid blinking, vocal instability

## Data Format

The dataset is provided as a JSONL file where each line contains:

```json
{
  "messages": [
    {
      "content": "System prompt with task instructions...",
      "role": "system"
    },
    {
      "content": "<video>",
      "role": "user"
    },
    {
      "content": "",
      "role": "assistant"
    }
  ],
  "videos": ["https://..."],
  "multilabels": ["Signal1", "Signal2", ...],
  "video_id": "unique_video_identifier.mp4"
}
```

## Usage

```python
from datasets import load_dataset

# Load dataset
dataset = load_dataset("Interhuman/wave1-test-set", split="train")

# Or load the raw JSONL file
import json

with open("configs_wave1-test-set-dataset.jsonl", "r") as f:
    data = [json.loads(line) for line in f]

# Access first sample
sample = data[0]
print(sample['video_id'])
print(sample['multilabels'])
print(sample['videos'][0])
```

## Dataset Statistics

- **Total Samples**: 50
- **Multi-label Classification**: Each video can have multiple social signals
- **Signal Distribution**: Varies across samples

## Citation

If you use this dataset, please cite:

```bibtex
@dataset{interhuman_wave1_test,
  title={Wave1 Test Set - Social Signal Detection},
  author={Interhuman},
  year={2024},
  publisher={Hugging Face}
}
```

## License

Apache 2.0