Inspiration
The inspiration for SocSync came from the chaotic world of university life, where students like us are constantly juggling classes, clubs, and social events. As students at the University of Sydney, we found ourselves overwhelmed by the scattered event information across various platforms - Instagram and Facebook posts, society websites, and word-of-mouth announcements. It was frustrating to miss out on great opportunities because we couldn't keep track of everything. We realized that many students face the same issue: discovering events is time-consuming and inefficient, leading to lower participation in campus activities. This sparked the idea for SocSync - a centralized platform that automates event aggregation and makes discovery effortless. We wanted to create something that not only solves a real problem but also enhances the social fabric of university life by connecting students with meaningful experiences.
What it does
SocSync is a comprehensive event discovery platform designed specifically for university students. It automates the aggregation of events from multiple sources, including social media posts from societies and clubs. Using AI-powered information extraction, it parses event details like titles, descriptions, dates, locations, and perks (such as free food or prizes) from unstructured data. Users can then apply smart filters to find events based on interests, costs, and more. The platform features a live map integration that shows events geographically, so students can locate the respective events easily. Additionally, users can save favorite events and receive personalized recommendations to join an event or follow a society. SocSync transforms the fragmented event landscape into a unified, user-friendly experience that boosts student engagement and participation in campus life.
How we built it
We built SocSync using a modern tech stack to ensure scalability and performance. The frontend is powered by Next.js 14 with TypeScript, providing a robust framework for server-side rendering and component-based architecture. For styling, we used Tailwind CSS to create a clean, accessible interface. The backend leverages Supabase for database management and authentication, allowing seamless user accounts and data storage.
The core innovation lies in the automated event aggregation system. We used a Python-based scraper using libraries like Selenium and BeautifulSoup to crawl Instagram and other sources for event data. To extract structured information from messy social media posts, we integrated AI-powered parsing with OpenAI's GPT models, which intelligently categorizes events by type, date, location, and perks. This data feeds into smart filtering algorithms that allow users to discover events based on interests, proximity, and availability.
For the live map integration, we incorporated Mapbox to visualize events geographically, with real-time routing and location autocomplete. We used Git for version control throughout the development process. The project follows a modular architecture, with separate concerns for scraping, data processing, and UI rendering, making it maintainable and extensible.
Challenges we ran into
Building SocSync wasn't without its hurdles. One of the biggest challenges was dealing with the unstructured nature of social media data - Instagram posts often contain inconsistent formatting, emojis, and abbreviations that made reliable information extraction difficult. We spent considerable time refining the AI prompts and adding fallback parsing logic to handle edge cases, ensuring at least 80% accuracy in event details.
Another significant obstacle was integrating the map functionality with real-time data. Balancing performance with user experience required optimizing API calls and implementing caching strategies to prevent slow load times. Additionally, as a team of developers, coordinating the full-stack complexity while learning new technologies on the fly was demanding. We faced authentication issues with Instagram's API changes, which forced us to pivot to alternative scraping methods, highlighting the fragility of third-party integrations.
Time constraints during the hackathon added pressure, but they taught us to prioritize features and build MVPs effectively. Debugging the scraper in a headless environment and ensuring cross-platform compatibility were also learning experiences that tested our problem-solving skills. Despite these challenges, each setback led to better solutions and a more resilient product.
Accomplishments that we're proud of
We're incredibly proud of creating a functional, end-to-end platform that addresses a real pain point for students. Successfully implementing AI-driven data extraction from social media was a major win, as it automates a previously manual and error-prone process. The live map integration stands out as a user-friendly feature that makes event discovery intuitive and location-aware. We're also proud of our modular architecture, which allowed us to iterate quickly and maintain code quality under tight deadlines. Finally, receiving positive feedback from fellow students during testing validated that SocSync fills a genuine need and has the potential to increase campus event participation.
What we learned
Throughout this project, we gained invaluable insights into full-stack development, data processing, and user experience design. Technically, we deepened our knowledge of Next.js and TypeScript for building responsive web applications, while exploring Python for web scraping and AI-driven data extraction. We learned about integrating APIs like Supabase for backend services and Mapbox for location-based features. On the non-technical side, we discovered the importance of user-centered design—conducting informal surveys with fellow students helped us prioritize features that truly matter. We also learned about the challenges of handling unstructured data from social media, which taught us about data cleaning and natural language processing basics. Perhaps most importantly, we learned the value of iterative development: starting small, testing frequently, and refining based on feedback. This project reinforced that building software is as much about problem-solving and empathy as it is about coding.
What's next for SocSync
Moving forward, we plan to expand SocSync with several exciting features. We'll implement personalized recommendations using machine learning to suggest events based on user behavior and preferences. Adding social features like event sharing, reviews, and community forums could enhance user engagement. We're also exploring partnerships with university societies for direct API integrations to improve data accuracy. On the technical side, we'll optimize the AI extraction for better performance and add support for more event sources. Long-term, we envision SocSync as a comprehensive campus life platform, potentially including study group matching and resource sharing. Our goal is to scale SocSync to other universities, making it a go-to tool for student communities everywhere. This experience has solidified our passion for building impactful software that makes a difference in people's daily lives.
Log in or sign up for Devpost to join the conversation.