Inspiration

Usually when I look for movies it always has to be through a friend or through a list online populated with 10's of movies. If a tinder-like app for movies can grow then it can be very helpful in discovering movies since we can examine each other individually and (in the future) see a trailer for each movie!

What it does

Shows a user a movie (currently from the most popular list) with the rating and descriptions. The user can like it to save it to their list for possible options, or dislike it to skip.

How we built it

Using react.js, HTML/CSS

Challenges we ran into

Getting asyc functions to work, styling it to match our vision, time constraints since we were only able to code the basic functionality of it. We also felt like giving up many times but somehow we stayed persistent and finally completed something. ☺

Accomplishments that we're proud of

We made a working app and we hosted it through Vercel, and registered a possible domain for it: movietime.tech

What we learned

First we spent hours making a chrome extension but although we ended up failing due to the main constraints that we learned a chrome extension had, we got lots of useful experience with Javascript and the structure of web apps. Our next idea was this web-app that helps users discover their next movie through which we learned and solidified our react, css, and html skills.

What's next for Movie Time ☺

  • Expanding the dataset to have access to a much wider range of movies.
  • Allowing the user the option to see detailed reviews about the movie.
  • Replacing the movie cover with an actual trailer that the user can watch to get the most accurate feel for the movie.
  • Adding detailed genre categorization.
  • Adding streaming services that its available on.
  • Adding robust parental guidance filters (this is often hard to come by in many movie databases)
  • Moving this prototype to be on a mobile device, and having a UI similar to a dating app where the user can swipe right on movies they find interesting, swipe left on ones they don't, and swipe up to see more information. This can help tailor recommendations without the user needing to spend time watching every movie for it to count.
  • Adding more specific tabs such as watch later, already watched, and loved (after watching), all of which can be users to further tailor recommendations.
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