Test the website:
https://cloudykrypton.github.io/CloudyKrypton/schulich/tester.html
Link to project slides:
https://docs.google.com/presentation/d/1A_VASAO9GQmjYsvOyHst35x6leVgrCUoV0WaSoNXmD4/edit?usp=sharing
Inspiration
We liked the idea of representing Chinese "influence" over a map (using follower count as a metric) with proportionally sized circles over given regions/countries.
What it does
We created an interactive webpage that represents the Chinese government's social media presence and influence in various regions across a map of the world using circles sized proportional to the number of followers that entities owned/hired by the Chinese government have amassed in the area. Clicking on any of the circles will cause more specific data to show up, along with a pie chart that shows how the region's follower count is distributed amongst different groups within the Chinese government.
How we built it
Data cleaning/processing: We utilized the pandas Python library to extract and manipulate the provided dataset. First, we grouped the data by Region of Focus and calculated the total amassed following for each region. Since we wanted to provide a high-level overview of China's social media influence, we discarded data related to regions in which the Chinese government had amassed a total social media following of < 10,000. Then, for each region, we determined the owner entities (entities that owned the accounts that were amassing followers) that were present in the region, and the following that each of them had amassed in that region. We used this data to calculate the area of the pie chart a given owner entity would be allocated. Finally, we applied a logarithmic scale to each region's total follower count, which we used to appropriately size the circles on our map.
Data visualization: We built a webpage with HTML/CSS and JavaScript to display a visually appealing and interactive map, with circles representing the Chinese government's social media following for a given region.
Challenges we ran into
Entering this hackathon, we were both pretty new to data visualization. We had to learn and develop fluency with the pandas library, figure out how to get our processed data onto a webpage, and learn the JavaScript needed to display our data in a visually impressive and interactive way.
Accomplishments that we're proud of
We're happy that we finished all the goals that we set out for this project. In particular, getting the pie charts to show up correctly on our webpage was a big moment of celebration for us.
What we learned
We're also proud that we got the opportunity to familiarize ourselves more with the languages and libraries that we used for this project, like JavaScript, CSS and the pandas Python library.
What's next for Influencer Data Visualizer
Our webpage could definitely use a few stylistic and visual touchups, since it was a bit of a rushed job. Moreover, to further represent the dataset that we were given, we could add "deeper" layers to each region's pie chart; that is, for each of the entity owners, we could show the distribution of its amassed follower count across each of the entity owner's individual accounts.
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