They say a picture's worth a thousand that case a GIF must be worth at least two thousand, possibly more. As a team, we were awed and inspired by this power, and how far we could push this technology. There is an inherent spiritual connection you forge with yourself when you write in a diary, and we encourage you all to use our web app, in order to take a step back and notice the bigger GIF of your life.

What it does

Our web app analyzes the users journal entries, extracts the main keywords, and discerns the main emotions behind the journal entries. Our web app then utilizes these profound results to conjure the perfect GIF describing the user's experiences, summarizing an entire diary entry with a single GIF. Our web app then offers several tools to help manage this information: for instance plotting emotional trends and analyzing sentiment data over time.

How we built it

We used IBM's Watson API to analyze tone and then implemented a keyword-extractor to most effectively associate journal entries with emotions and important words. Then, we provided these calls to Giphy's API to return an appropriate GIF and finally incorporated a mathematical solution to graph the data in a simple yet elegant display on a node.js localhost server.

Challenges we ran into

Integrating more than one API proved to be a difficult task, as well as storing past journal entry data with google's chrome cookies. In addition,because of time constraints, we weren't able to construct a visual display as enticing as we had hoped.

Accomplishments that we're proud of

We are proud of creating a project with node.js, a platform none of us had ever used before. In addition, we are proud of creating an unique idea that we feel will be a beneficial asset to the world.

What we learned

We learned a lot about the technology we used- namely node.js and Watson APIs, insight into CS principles such as the client-server model, and cooperation skills through working with teammates.

What's next for GLIFE

We hope to include more informative data analysis and visualization, create a more user friendly display, and possibly including machine learning to further tailor this web app to specific individuals

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