Inspiration
We were curious to dive into Foreign Interference, and where this interference was coming from, who it's targeting, and how big a role it truly plays. We wanted to map and understand the relationships and context between our data, using a data driven, interactive, presentation.
What it does
This presentation provides a comprehensive analysis, along with many visualizations regarding these foreign entities. We hope these visualizations truly show how big the entities in the network participating in foreign interference really is, as well as some discussion in the presenter notes about the implications and context. We also tried to make it as interactive as possible, for people with all sets of knowledge, starting with foundational information and quizzes, as well as professional transitions and eye catching graphics from DALL-E to maintain user attention. Note that in order to view the presentation how it is meant to be viewed (with all transitions and effects), it should be downloaded from the GitHub repository, rather than viewing on Google Slides.
How we built it
We used Python libraries such as matplotlib, pandas, numpy, networkx, and a couple others to examine our data, and create visually appealing diagrams representing what we found, while highlighting the vast importance and scale of foreign interference issues.
Challenges we ran into
One of the main challenges was accurate representation of the data, while maintaining readability and visual appeal. We found ourselves, for example, having to only label the top 5 largest entities in our network diagram, as there were too many entities otherwise.
Accomplishments that we're proud of
We are proud of our diagrams, as we tried our best to make them as visually appealing as possible, while underlying their importance.
What we learned
Our data science skills definitely improved, but more importantly, we've never truly realized the scale and influence surrounding foreign interference, and how it is such a big issue, until examining the data and research.
Built With
- basemap
- dalle
- excel
- matplotlib
- networkx
- numpy
- pandas
- powerpoint
- python
- seaborn
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