Inspiration
Inspiration We were inspired by the undeniable link between mental well-being and professional productivity. In a world where young adults face increasing pressure, existing solutions often treat mental health and career development as separate issues. We wanted to build a single, compassionate platform that addresses both in a seamless, stigma-free way. Our goal was to create a digital companion that doesn't just track your feelings but actively guides you toward feeling better and moving forward with personalized, actionable advice.
What it does
How we built it
Frontend: HTML5, CSS3, and vanilla JavaScript for a lightweight, fast experience.
Data Visualization: Chart.js for building the interactive mood and stress timeline graphs.
Data Storage: The browser's localStorage API to keep all user data private and secure on their device.
Sentiment Analysis Engine: We built a custom engine in JavaScript that uses keyword matching with extensive libraries of positive and negative words to analyze user input and calculate a sentiment score and polarity.
Design: A custom UI/UX design was created from scratch to be calming, intuitive, and engaging.
Challenges we ran into
Accomplishments that we're proud of
Creating a Fully Functional App in a Sprint: Delivering a complex, feature-complete application with custom AI, data visualization, and a unique character system in just over 8 hours.
Prioritizing User Privacy: Building a system that respects user data by keeping everything client-side, with no backend or data collection.
Seamless Integration: Successfully merging the two domains of mental health support and career development into one cohesive, natural user experience.
The Character System: Designing four lovable and distinct characters that users can genuinely connect with for different types of support.
What we learned
the Power of Vanilla JS: We deepened our understanding of advanced JavaScript concepts and how to build complex features without heavy frameworks.
UI/UX for Mental Health: Designing for an application in this space requires a special emphasis on empathy, tone, and simplicity to avoid overwhelming the user.
Algorithm Design: Creating even a simple sentiment analysis algorithm from scratch provides invaluable insight into the world of Natural Language Processing (NLP).
Project Scoping: We learned to effectively scope a project for a hackathon, balancing ambition with what is achievable within a tight deadline.
What's next for micromood
Expanded Task Library: Building a much larger database of micro-tasks and resources for both mental health and career growth.
Advanced NLP: Integrating a more sophisticated natural language processing API for even more accurate sentiment and theme detection (e.g., detecting anxiety about interviews vs. anxiety about social situations).
Push Notifications & Scheduling: Implementing gentle, reminder-based check-ins to help users build a consistent habit.
PWA Implementation: Packaging MicroMood as a Progressive Web App (PWA) so users can "install" it on their phones for easier access.
Community Features (Optional & Privacy-Focused): Exploring anonymized, opt-in features where users can see aggregate data about common stressors or share encouraging messages.
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