## Inspiration

We were all chronically addicted to Reddit, and all the productivity extensions out there took a "cold turkey" approach. We felt like our method of gradual addiction treatment is more effective.

## What it does

Over time, we slowly remove elements on reddit that are addicting (CTA's, voting counters, comment counts, etc.). This way, the user willingly develops indifference towards the platform opposed to fighting the hard wired behaviour that Reddit expertly ingrained.

## How we built it

We performed research on how drug rehabilitation is performed at rehab centres, and incorporated those practices into the design of the extension. We used jQuery to manipulate the DOM elements.

## Challenges we ran into

Time was the main constraint, as we spent the first half of the hackathon discarding dead-end ideas midway.

## Accomplishments that we're proud of

Finishing in time and shipping an application that can be used immediately by other addicted redditors.

## What we learned

jQuery and better familiarity with building chrome extensions.
## Inspiration

One of our team members, an international student from India, shocked us with troubling statistics about the organ donation infrastructure in his home country. Where 200,000 people need new kidneys and 100,000 need new livers each year, only **around 2%** actually receive them. This figure is a product of bureaucratic red tape and inefficient donor matching. Though the system in the United States is far from perfect, we take the associated medical infrastructure almost for granted. We were truly humbled by this realization and spent our Pennapps trying to tackle this problem in any way possible.

## HOW SODA WORKS

In developing countries (such as India) where there is little existing infrastructure for electronic patient records as well as a lack of an efficient emergency organ donation system, SODA serves as a comprehensive web application to store patient records online, efficiently and rapidly match available organs (in the case of accidental death) to nearby acceptors based on a host of medical factors such as disease history, blood type, behavioral patterns and other significant elements. SODA's is grant thousands of organ recipients a second chance at life and save many more lives!
SODA provides an online infrastructure for hospitals to store information necessary for patients receiving and giving organ transplants and match viable candidates using a prioritization algorithm. Hospitals create accounts on the webapp and register patients in lists of donors and acceptors through a detailed form. If a donor passes away and their organs are avavilable, a separate form feeds into an organ-acceptor matching algorithm to determine the viable locations and candidates.

## How we built it

HTML/CSS, Google Maps API, Python/Flask, Bootstrap, MongoDB, Github

## Challenges we ran into

-Setting up the database backend
-Building an efficient matching algorithm, when none of us had a medical/biology background

* Conflicting CSS schemes
* Multiple people editing template files

## Accomplishments that we're proud of

Putting our research efforts to good use by using the data we collected to make a comprehensive medical form for patients (Donors and Acceptors) and organ matching algorithm.
Pulling through at 5 am with the database component with no prior experience and building a successful, non-local database (MongoDB)

## What's next for Soda

Amazon Alexa!
According to a study, many doctors spend 2/3 or more of their daily schedule filling out paperwork. We originally explored integration of organ donation checklists with Alexa, but based on our interests and priorities, decided to focus solely on the web app for this hackathon. In the future, we would like to link voice control to the patient medical database to save doctors energy and time. Furthermore, Alexa could ask patient history questions and tabulate answers so as to use this data to determine whether a person is an eligible donor for an organ as well to find the optimal acceptor match.
## Inspiration

We wanted to allow financial investors and people of political backgrounds to save valuable time reading financial and political articles by showing them what truly matters in the article, while highlighting the author's personal sentimental/political biases.
We also wanted to promote objectivity and news literacy in the general public by making them aware of syntax and vocabulary manipulation. We hope that others are inspired to be more critical of wording and truly see the real news behind the sentiment -- especially considering today's current events.

## What it does

Using Indico's machine learning textual analysis API, we created a Google Chrome extension and web application that allows users to **analyze financial/news articles for political bias, sentiment, positivity, and significant keywords.** Based on a short glance on our visualized data, users can immediately gauge if the article is worth further reading in their valuable time based on their own views.
The Google Chrome extension allows users to analyze their articles in real-time, with a single button press, popping up a minimalistic window with visualized data. The web application allows users to more thoroughly analyze their articles, adding highlights to keywords in the article on top of the previous functions so users can get to reading the most important parts.
Though there is a possibilitiy of opening this to the general public, we see tremendous opportunity in the financial and political sector in optimizing time and wording.

## How we built it

We used Indico's machine learning textual analysis API, React, NodeJS, JavaScript, MongoDB, HTML5, and CSS3 to create the Google Chrome Extension, web application, back-end server, and database.

## Challenges we ran into

Surprisingly, one of the more challenging parts was implementing a performant Chrome extension. Design patterns we knew had to be put aside to follow a specific one, to which we gradually aligned with. It was overall a good experience using Google's APIs.

## Accomplishments that we're proud of

We are especially proud of being able to launch a minimalist Google Chrome Extension in tandem with a web application, allowing users to either analyze news articles at their leisure, or in a more professional degree. We reached more than several of our stretch goals, and couldn't have done it without the amazing team dynamic we had.

## What we learned

Trusting your teammates to tackle goals they never did before, understanding compromise, and putting the team ahead of personal views was what made this Hackathon one of the most memorable for everyone. Emotional intelligence played just as an important a role as technical intelligence, and we learned all the better how rewarding and exciting it can be when everyone's rowing in the same direction.

## What's next for Need 2 Know

We would like to consider what we have now as a proof of concept. There is so much growing potential, and we hope to further work together in making a more professional product capable of automatically parsing entire sites, detecting new articles in real-time, working with big data to visualize news sites differences/biases, topic-centric analysis, and more. Working on this product has been a real eye-opener, and we're excited for the future.