MovieMovie

Inspiration

It is almost impossible to judge movie's quality just by the title or description. We tend to ask our friends for advice, but what if they are not around? We make it easier then ever before by compiling and delivering a feed to the user from different social media about the film of choice. It is really a nice in order to estimate whether the film is worth watching before buying it. MovieMovie will deprive you of disappointment.

What it does

It extends the existing features of the Elisa web interface. A user coming to the main page is presented of the selection of the top movies, based on his personal needs. When one selects a film, in addition to its description we provide the selected messages integrated from various social media, which show positive and negative mentions of the film. This is done by using sophisticated sentiment analysis. In addition to that similar movies are recommend, maybe they will have a better feedback.

How we built it

Built from the ground up to support webscale. Distributing the microservices with docker and HTTP. We are scraping the web's social media platforms, movie review sites and leveraging the power of AI to process the data with natural language processing.

Challenges we ran into

We had so many ideas how to extend our functionality but to the lack of time could not implement them all!

Accomplishments that we're proud of

It works! We would be happy to use it ourselves!

What we learned

We learned how to work in a team efficiently and how to tailor our work to fit into submission deadlines

What's next for MovieMovie

Many extensions (integrating more media) and conceptual changes (offering further info to user, like the awards of the film). Another idea is to device a search for a movie through the messages on reddit which fit into some criteria.