Inspiration

BuzzFeeder was created to provide a social browsing experience. The Chrome Extension connects with your Facebook friends and gives you a customized list of articles, lists and other BuzzFeed pages that your friends have recently viewed, allowing you to follow what your friends are viewing. This will keep people on the website for longer and clicking on more articles in addition to creating a more pleasant user experience.

How it works

We created a Chrome Extension that uses Facebook authorization to allow access to the Friend list, profile picture, and Facebook name. It then tracks any URL's opened in Chrome; if the URL is a BuzzFeed article it is saved to our database, associated with the Facebook user. Your friends' BuzzFeed site visits are shown in a real time highly-responsive activity feed for you to see.

## Challenges I ran into Initially we wanted to incorporate the use of Facebook' "Likes" to populate the customized timeline. We decided to take this idea on a tangent but with the same end goal.

Accomplishments that I'm proud of

We initially were skeptical about our technical skills and whether we would be able to create a hack or not. However, despite having a wide ranging skill set, we all contributed to the final project in different ways.

What I learned

The team members who were not confident in their coding skills were able become more proficient various languages. We were also learned that there are so many online resources and readily available frameworks that makes it easy to make a minimum viable product in a short time period.

What's next for BuzzFeeder

We would like to incorporate more analytics and to integrate with the main BuzzFeed site, giving us a wider reach for the extension. Once we have a wider reach, we can perform more analytics on interactions with Buzzfeed articles happening on other websites (Facebook, Twitter, etc.).

Heat index that suggests articles based on amounts of interactions (read, shares, likes) from friends.

Would also be cool to get article Reaction data so that the view includes a preview of the article type.

Notifications can be added but it must be considered that it could be overwhelming. Possibly based on heat index or following specific users activity feed.

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