Movie Mania


Big data has become commonplace throughout the modern world. From media company libraries to storefront sales and inventories, all require working with vast quantities of data. The goal of the project is to break into this widely used field and develop an app centered around the aggregation and searching of big data. The project utilizes three main technologies: Elasticsearch, MovieLens, and TheMovieDb. Elasticsearch is the distributed search and analytics engine at the heart of the Elastic Stack. MovieLens is a 25M size dataset of movie tag and rating data collected from anonymous users. TheMovieDb is a database of up-to-date movie-related data. Combining these technologies, the project brings to users a new movie discovery app, MovieMania, that offers a unique experience of selecting tags via word cloud to selectively hone in on what each user is looking for in that moment. The app also includes typical features such as account creation, saving of tags to user-defined lists for later perusal, and more general browsing options such as by what is popular.


Community Benefit

The project offers benefits to multiple communities. The watchers will gain a new interactive means of browsing for movies. The scale and variety of tags brings unique spins to any user's path of browsing. Users can select one tag at a time to narrow down exactly what they are looking for, until either a single movie or list of suitable films remains. The filmmakers will gain representation, as the path any tag list may be formed is undiluted by influence and marketing campaigns. The students who partook in the creation of the app will gain knowledge and experience working with a modern system utilized throughout the business world.


Team Members

Siobahn Devlin 

Ethan Fleming 

Kevin Horta 

Dominique Nelson 


Sponsored By

Dr. David Jaramillo