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| title: OnCoCo Message Classifier | |
| emoji: 🧠 | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: 6.10.0 | |
| app_file: app.py | |
| pinned: false | |
| license: cc-by-4.0 | |
| short_description: Classify psychosocial online counseling messages | |
| tags: | |
| - text-classification | |
| - counseling | |
| - mental-health | |
| - multilingual | |
| - german | |
| - english | |
| # OnCoCo Message Classifier | |
| This Space provides an interactive demo for classifying individual messages from psychosocial online counseling conversations into fine-grained categories. | |
| ## What it does | |
| Given a single counseling message — prefixed with the speaker role (`Counselor:`, `Client:`, `Berater:`, or `Klient:`) — the model predicts the most likely communication act categories and their confidence scores. | |
| Categories cover 40 counselor acts (e.g. empathic reflection, problem exploration, motivational interviewing techniques) and 28 client acts (e.g. expressing emotions, describing problems, requesting information). | |
| ## Model | |
| [th-nuernberg/xlm-roberta-base-online-counseling-oncoco](https://huggingface.co/th-nuernberg/xlm-roberta-base-online-counseling-oncoco) | |
| A fine-tuned XLM-RoBERTa model trained on the OnCoCo dataset using 5-fold stratified cross-validation. | |
| ## Dataset | |
| [th-nuernberg/OnCoCoV1](https://huggingface.co/datasets/th-nuernberg/OnCoCoV1) | |
| OnCoCo (Online Counseling Conversations) is a bilingual (German/English) corpus of annotated psychosocial online counseling messages. Topics include mental health, relationships, substance use, and financial problems. | |
| ## Usage | |
| Select one of the provided examples or enter a custom message. Prefix the message with the appropriate role marker: | |
| - `Counselor:` / `Berater:` for counselor messages | |
| - `Client:` / `Klient:` for client messages | |
| Use the Top-K dropdown to control how many top predictions are shown. | |
| ## Citation | |
| If you use this demo or the underlying dataset/model in your research, please cite the associated publications (see the dataset card for details). | |
| ## License | |
| CC BY 4.0 — Technische Hochschule Nürnberg, Jens Albrecht | |