Flicks & Flirts!

Inspiration

Our hackathon project idea was to create a website called Flicks & Flirts. We were inspired by the concept of combining personality quizzes and movie recommendations, similar to the format of Tinder. Users would take a personality quiz, and based on their answers, they would receive movie recommendations tailored to their personality.

Flicks & Flirts is a website that allows users to discover personalized movie recommendations based on their personality. Users can take a personality quiz and the website will provide them with movie suggestions that align with their preferences and characteristics.

We built Flicks&Flirts using a combination of front-end and back-end technologies. The front-end was developed using HTML, Cinemangoer. We created a user-friendly interface for the personality quiz and the display of movie recommendations. For the back-end, we utilized a database to store user responses and movie data. We also implemented algorithms to match user personalities with appropriate movie recommendations.

During the development of Flicks&Flirts, we encountered several challenges. One of the main challenges was designing and implementing the personality quiz algorithm to accurately match users with movie recommendations. Additionally, integrating the front-end and back-end components required careful coordination and troubleshooting.

We are proud of successfully creating different aspects of the Flirts&Flicks within the timeframe of the hackathon, as well as working together as a team, and figuring out our strengths and weaknesses and how to adapt to it. We were able to develop a user-friendly interface, implement the personality quiz, and provide accurate movie recommendations based on user responses. Moreover, we created an intuitive and visually appealing design for the website.

Throughout the development process, we gained valuable experience in front-end and back-end web development. We learned how to design and implement a personality quiz, integrate databases for storing user data, and utilize algorithms for personalized recommendations. Additionally, we improved our teamwork and collaboration skills by working together on a complex project. We also learned the importance of being organized and having a solid plan to follow, as well as having a plan on how we are gonna approach the problem, and staying on track and working together to meet each other’s need.

In the future, we plan to further enhance Flicks&Flirts by expanding the movie database and refining the recommendation algorithm. We also aim to incorporate user feedback and implement additional features such as user profiles, social sharing, and personalized movie playlists. With continuous development and improvement, we hope to provide an engaging and enjoyable movie recommendation experience for our users.