## Inspiration

The most important part in any quality conversation is knowledge. Knowledge is what ignites conversation and drive - knowledge is the spark that gets people on their feet to take the first step to change. While we live in a time where we are spoiled by the abundance of accessible information, trying to keep up and consume information from a multitude of sources can give you information indigestion: it can be confusing to extract the most relevant points of a new story.

## What it does

Macaron is a service that allows you to keep track of all the relevant events that happen in the world without combing through a long news feed. When a major event happens in the world, news outlets write articles. Articles are aggregated from multiple sources and uses NLP to condense the information, classify the summary into a topic, extracts some keywords, then presents it to the user in a digestible, bite-sized info page.

## How we built it

Macaron also goes through various social media platforms (twitter at the moment) to perform sentiment analysis to see what the public opinion is on the issue: displayed by the sentiment bar on every event card! We used a lot of Google Cloud Platform to help publish our app.

## What we learned

Macaron also finds the most relevant charities for an event (if applicable) and makes donating to it a super simple process. We think that by adding an easy call-to-action button on an article informing you about an event itself, we'll lower the barrier to everyday charity for the busy modern person.

Our front end was built on NextJS, with a neumorphism inspired design incorporating usable and contemporary UI/UX design.

We used the Tweepy library to scrape twitter for tweets relating to an event, then used NLTK's vader to perform sentiment analysis on each tweet to build a ratio of positive to negative tweets surrounding an event.

We also used MonkeyLearn's API to summarize text, extract keywords and classify the aggregated articles into a topic (Health, Society, Sports etc..) The scripts were all written in python.

The process was super challenging as the scope of our project was way bigger than we anticipated! Between getting rate limited by twitter and the script not running fast enough, we did hit a lot of roadbumps and had to make quick decisions to cut out the elements of the project we didn't or couldn't implement in time.

Overall, however, the experience was really rewarding and we had a lot of fun moving fast and breaking stuff in our 24 hours!
## About Us

Discord Team Channel: #team-64

omridan#1377,
dylan28#7389,
jordanbelinsky#5302,
Turja Chowdhury#6672

Domain.com domain: positivenews.space

## Inspiration

Over the last year headlines across the globe have been overflowing with negative content which clouded over any positive information. In addition everyone has been so focused on what has been going on in other corners of the world and have not been focusing on their local community. We wanted to bring some pride and positivity back into everyone's individual community by spreading positive headlines at the users users location. Our hope is that our contribution shines a light in these darkest of times and spreads a message of positivity to everyone who needs it!

## What it does

Our platform utilizes the general geolocation of the user along with a filtered API to produce positive articles about the users' local community. The page displays all the articles by showing the headlines and a brief summary and the user has the option to go directly to the source of the article or view the article on our platform.

## How we built it

The core of our project uses the Aylien news API to gather news articles from a specified country and city while reading only positive sentiments from those articles. We then used the IPStack API to gather the users location via their IP Address. To reduce latency and to maximize efficiency we used JavaScript in tandem with React opposed to a backend solution to code a filtration of the data received from the API's to display the information and imbed the links. Finally using a combination of React, HTML, CSS and Bootstrap a clean, modern and positive design for the front end was created to display the information gathered by the API's.

## Challenges we ran into

The most significant challenge we ran into while developing the website was determining the best way to filter through news articles and classify them as "positive". Due to time constraints the route we went with was to create a library of common keywords associated with negative news, filtering articles with the respective keywords out of the dictionary pulled from the API.

## Accomplishments that we're proud of

We managed to support a standard Bootstrap layout comprised of a grid consisting of rows and columns to enable both responsive design for compatibility purposes, and display more content on every device. Also utilized React functionality to enable randomized background gradients from a selection of pre-defined options to add variety to the site's appearance.

## What we learned

We learned a lot of valuable skills surrounding the aspect of remote group work. While designing this project, we were working across multiple frameworks and environments, which meant we couldn't rely on utilizing just one location for shared work. We made combined use of Repl.it for core HTML, CSS and Bootstrap and GitHub in conjunction with Visual Studio Code for the JavaScript and React workloads. While using these environments, we made use of Discord, IM Group Chats, and Zoom to allow for constant communication and breaking out into sub groups based on how work was being split up.

## What's next for The Good News

In the future, the next major feature to be incorporated is one which we titled "Travel the World". This feature will utilize Google's Places API to incorporate an embedded Google Maps window in a pop-up modal, which will allow the user to search or navigate and drop a pin anywhere around the world. The location information from the Places API will replace those provided by the IPStack API to provide positive news from the desired location. This feature aims to allow users to experience positive news from all around the world, rather than just their local community. We also want to continue iterating over our design to maximize the user experience.
## Inspiration

The media we consume daily has an impact on our thinking, behavior, and emotions. If you’ve fallen into a pattern of regularly watching or listening to the news, the majority of what you’re consuming is likely about the coronavirus (COVID-19) crisis.
And while staying up to date on local and national news, especially as it relates to mandates and health updates, is critical during this time, experts say over-consumption of the news can take a toll on your physical, emotional, and mental health.

## What it does

The app first greets users with a screen prompting them to either sign up for an account or sign in to a pre-existing account. With the usual authentication formalities out of the way the app gets straight to business as our server scrapes oodles of articles from the internet and filters out the good from the bad, before displaying the user with a smorgasbord of good news.

## How we built it

We have used flutter to create our android based application and used firebase as a database. ExpressJS as a backend web framework. With the help of RapidAPI, we are getting lists of top headline news.

## Challenges we ran into

Initially, we tried to include Google Cloud-Based Sentiment Analysis of each news. However, we thought to try some new technology. Since the majority of our team members were new to machine learning, we were facing too many challenges to even get started with. Issues with lack of examples available. So we again limited our app to show customized positive news. We wanted to add more features during the hacking period but due to time constraints, we had to limit.

## Accomplishments that we're proud of

Completely Working android based applications and integrated with backend having the contribution of each and every member of the team.

## What we learned

We have learned to fetch and upload data to firebase's real-time database through the flutter application. We learned the value of Team Contribution and Team Work which is the ultimate key to the success of the project. Using Text-based Sentiment Analysis to analyze and rank news on the basis of positivity through Cloud Natural Language Processing.

## What's next for Hopeful

1. More Customized Feed
2. Update Profile Section
3. Like and Reply to comments