Our team's goal was create something that would help others. Recently, we have all been impacted in some way with this year's election, and it has become clear that as citizens of this country, we will need to provide support and be open with one another more than ever before. From this, we drew the idea to create a website that would offer such a support structure and provide information that would generate discussion revolving around discrimination.

What it does

The website is interactive and allows users to input, if they so choose, their experience involving discrimination, the location at which it transpired, and the users' contact information. This website not only serves as a support structure and means of initiating meaningful conversation, but it also serves as a wealth of data. With the implementation of a time slider, discussed below, users can see the frequency at which users of the site report discriminatory acts. This has strong implications of how such problems can be addressed.

How we built it

The landing page of our website was built using Brackets so that HTML and CSS could be used in tandem. We incorporated some parts of the CSS library of Barrel, a website development based in New York. The animation was made using Adobe Illustrator and After Effects. The video was embedded in an iframe, and through HTML, viewable in an endless loop. The mapping and handling of data was dealt with using ArcGIS. Through this platform, we were able to upload CSV files, visualize the data on a map, and allow users to further add information by using our specific web application. ArcGIS placed many tools at our disposal, some of which include heat mapping and storing data in their own cloud. One particularly interesting feature is the Time slider. Given that the data has timestamps, the time slider allows users to see the data on the days on which they were posted. This offers much potential in data analytics. With information regarding density and frequency at which crimes involving discrimination occur, action can be taken to address the trends that are seen.

Challenges we ran into

Our original idea dealt more with the data analytics side; we wanted to see how discrimination has evolved over the years and if there were any patterns that could be seen from this data. We had originally wanted to use Twitter API to get tweets, filtered using keywords, regarding specific instances of discrimination or hate crimes. What we quickly realized is that getting this information was extremely difficult. Twitter only releases tweets from the past week and to their selective choosing. This problem put our work to a standstill and we decided that instead of investigating archived data, we would examine real-time data. Current challenges consist of being able to efficiently parse through the web and bring meaningful data to the web application.We used python and ruby's nokogiri to parse through certain websites and find keywords. The task is extremely difficult due to the many holes we must fill i.e. fake news articles, picking the correct location, which keyword(s) are used in what area and so forth. We were unable to finish the web scraper in time to use it for the application, however, links have been recovered, saved and reopened for scanning. There is room for a lot of improvement with the scraper and once completed, it would allow the application to run independently.

Accomplishments that we're proud of

We are all very proud of what we were able to create this weekend. We had some dead ends in the beginning and had even considered completely switching projects, but we are all glad that we continued. There were multiple milestones that we accomplished that we are very proud of. One was when we were able to set up the web application to take input from the users. This was a core foundation of our entire project, getting real information and stories that can cause a true difference. We were also very proud when the landing page of our website was done. A lot of work was put into the format, design, and animation. It also represented the culmination of our project.

What we learned

We learned a lot this hackathon. For some of us, this was the first website that we made. For others, this was the first attempt of parsing websites. We learned about API's, data visualization, and the immense resources that is available to us even as students. We also met other people from various schools, which is always a welcomed experience.

What's next for Voices of America

Our next two steps would be:

  1. Improve the story-telling aspect of the map. Ideally, when a user decides to tell their story they should be able to write in a big text box, with the option of adding pictures/videos and sharing the post to social media. We would also like other users to be able to directly comment on the story, providing support.
  2. Incorporate other data besides user input, such as tweets, Facebook posts, and news articles. These would be represented differently on the map, but would be incorporated into the heat map to give a fuller picture of the amount of discrimination in a certain area. This data would also allow the time stream function to go back farther in time. This would be a very interesting feature, because users could see how events today might be related to an increase or decrease in discrimination in their region from past years.
    1. Addressing how to manage the data. Assuming many users input data, eventually some of the data would have to be stored into a separate database.

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