Chicane: noun

1.) the use of trickery to achieve a political, financial, or legal purpose

2.) an obstacle on a path

3.) the absence of trumps in a hand of cards

Data Visualization

The augmented reality visualization was built by Milan, and represents the users tweeting about voter fraud in the week surrounding the 2020 US presidential election. The number of tweets made by each user, the number of retweets by each user, and the current status of their Twitter account (active, deleted, suspended) appears in the AR Android app. Milan used Unity, Vuforia, Python, and SQLite to build the display and process the data.

We sourced our data from this GitHub repo: https://github.com/sTechLab/VoterFraud2020

Website

To build the website, Aditya used HTML, CSS, and Javascript, with additional UX/UI embellishments from Bootstrap, external CDNs, Slick.js, and FontsAwesome.com. W3Schools provided some of the gradient color schemes. The website explains the visualizations, the project, and the team. Our websites are linked below.

Data Visualization

Our project focuses on tweets and retweets made in the first week of November that concern the topic of voter/electoral fraud in the 2020 election.

We created a Dash app that visualizes the top retweets during this period as well as trends in their velocity (i.e how fast they spread), as well as whether users retweeting such content were still active as of December. Our dashboard also takes a look at the URLs spread throughout this period. Khai used Python, Plotly, Dash and other python frameworks to create this we app.

The augmented reality visualization component represents individual users tweeting about voter fraud in the week surrounding the 2020 US presidential election. This social graph displays clusters of users by the number of tweets made by each user, the number of retweets by each user, and the current status of their Twitter account (active, deleted, suspended). The app is built for Windows, with plans to extend to Android soon. Milan used Unity, Vuforia, Python, and SQLite to build the display and process the data.

Check out our GitHub repos and demo videos using the provided links!

Tracks

We used Google Colab for the Google Cloud track, and registered http://chicane.online and http://visualizehaxahoya.tech for the Domain.com track . In addition, we incorporated several forms of data visualization in order to qualify for the related track.

Challenges we ran into

Aditya: I was not able to load the Bootstrap part at the starting but I was able to do it.

Milan: Towards the beginning of the project, I had the sinking realization that I no longer had access to any of my course notes on natural language processing, but I managed to pivot. In the middle of the project, I realized that we had almost too much data to feasibly work with, and I was forced to reduce the scope of my visualization. Towards the end, the Vuforia configuration I was using stopped working a few times, which caused me a great deal of stress.

Accomplishments that we are proud of

Our team is proud that we completed everything on time. As our team was international, we had to contend with significant time differences, but we were still able to connect with each other and complete our project.

What's next?

Milan: I am interested in visualizing tweets from a longer time period, and creating connections between users to represent how tweets are shared among social networks. I would also be interested in creating an interactive component, improving the color scheme, and successfully deploying the app for Android.

Aditya: Till now we dont have anything in mind to bring change in Voter Fraud Visualization. But yes we will be soon thinking on taking it to the next level and push out more fraud tweets.

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