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Personal Journey_1
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The Anxiety Time Machine

See your current worries through the lens of the future.

Built by Boyi Sun, Ruoyu Wu and Xiaoyue Yu for She Innovates 2026.

Inspiration

As college students, we often feel overwhelmed by anxiety—whether it relates to grades, relationships, or financial stability. In the moment, these problems feel insurmountable. However, we realized that these same issues might look completely different to someone who is 30, 60, or 90 years old.

We built The Anxiety Time Machine to bridge the gap between generations. Our goal is to provide perspective and relief to anxious minds by showing how priorities and viewpoints shift over a lifetime.

📋 What it does

The Anxiety Time Machine is a web-based emotional sharing platform that helps users express and process their feelings while discovering they're not alone in their experiences. The platform provides a safe space for emotional expression through three distinct pathways:

Anxiety Sharing Channel: A dedicated space where you can write down your current anxieties and worries. After sharing, you'll experience a concise overview of anxiety patterns across different age groups, helping you understand how perspectives on similar concerns evolve throughout life's journey.
Happiness Sharing Channel: A positive environment where you can celebrate and share your happy moments and achievements. The platform provides insights into happiness patterns across various age groups, revealing how sources of joy and fulfillment shift and transform over time.
Personal Journey: A personalized dashboard where you can track and reflect on your own emotional history. View your complete timeline of shared anxieties and happy moments, analyze your most frequent emotional themes through interactive statistics, and filter your experiences by time period or message type. This feature helps you recognize patterns in your own emotional journey and see how your concerns and joys have evolved over time.

The platform transforms personal emotional experiences into a collective narrative, helping users understand that anxiety and happiness are shared human conditions that connect us all.

✨ Key Features

User Features

User Registration & Login: Secure user authentication system
Emotional Topic Selection: Users can choose from three main features:
- 😰 Anxiety - Share your anxiety and see others' anxiety
- 😊 Happiness - Share your happy moments and see others' happiness
- 👀 Browse - View shared emotional experiences without posting
Personal Journey: Track your emotional history with timeline and statistics

Core Pages

Home Page: Application entry point
Register Page: New user registration
Login Page: Returning user login
Dashboard Page: Main hub for emotional sharing and navigation
Share Anxiety Page: Share and browse anxiety emotions
Share Moments Page: Share and browse happy moments
Browse Page: Explore shared emotional experiences
Personal Journey Page: View your emotional history, timeline, and statistics

🛠️ Tech Stack

Frontend

React.js - User interface framework
JavaScript/JSX - Programming language
CSS - Styling

Backend

Python Flask - Backend framework
SQLite/SQL - Database

Development Tools

Node.js & npm - Package management
Git - Version control

Database Design

Main Tables - User Table

id
nickname
password
age
gender
tag
description
message_id -- distinguish between anxiety message and happiness message ## User Flow

Home Page → Register/Login → Main Page → Select Topic → Share/Browse Emotions

New users visit the home page and choose to register
Returning users login directly
After login, enter the main page and select one of three topics
Share your emotions or browse others' shares on the corresponding topic page

Challenges we ran into

How to create a reasonable and effective schema for the whole system. To simplify the process of retriving data, we only use one table to store data points. In long term use, we would decomposite the huge table into small tables.
Given the constraints on time and project scope, we conducted a targeted literature review to curate a high-quality, representative dataset.