whats_hAPPnn

The Idea

Clowns sightings on campus. There’s a quiz in biology class. BBQ in the quad at 4:30pm.  These are the things that students need to know in real time. 

whats_hAPPnn is a fast news app based on YikYak that allows people to anonymously post about things that are happening in their local area. By upvoting and downvoting, people can find which news is credible while also internally the system builds their anonymous credibility to improve the reliability of news.

This allows the news of smaller events to travel extremely fast around a large campus like UMass.  Local news stations need to confirm news stories before they can air them. With whats_hAPPnn news can get to your pocket faster than any other media.

This app is great at letting minimal advertised events around campus become known.  Every user only gets one vote per post.  The data is saved on a MONGO DB cloud based back up.  If posts get too many down votes it will be removed from the blog.  Users can login through Facebook but their posts will still remain anonymous.  Posts get deleted when they become irrelevant, currently it will get deleted after 24 hours.

Future Extensions

As it's built with Meteor, our app can be easily deployed to Android and iOS with little hassle and plenty of open-source technologies. The features we would like to add given more time would include more advanced sorting algorithms (like Reddit or HackerNews) that sorts posts according to both accuracy and recency, as well as a more dynamic UI for sorting between posts by location (i.e. different parts of a student campus) and by topic (perhaps for posting regular news, academic news, extracurricular news, etc.) In addition, there is the possibility of adding a comment system to broaden the amount of interaction between users and allow users to provide updates to developing stories.

As our app stands, there is no current moderation system, so it has to rely on the good intention of its users. When scaling our app, we would ideally implement a system to filter our repeat posts, and negatively value the votes of users who aren't reflecting the accuracy of most posts (ex. if somebody down votes accurate news stories, then they would have no credibility and the app would reflect this without them knowing).

We are looking to pursue publishing our app following the hackathon! We all had a great time working on this app, and we'd love to see it hit the market.

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