Twitter Cow | Devpost

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Inspiration

Traveling is something many people like to do, so how can we find the statistically best places for one to travel to. We wanted to tackle this using mathematical analysis and web-scraping techniques.

What it does

Using statistical analysis of social media postings in relation to popularity and favour, we established an algorithm in order to relate post popularity and travel destination popularity.

How we built it

Using snscraper to scrape social media websites for analytics, we utilized it as a way to gather data from twitter in order to determine a numerical rating on the popularity and quality of the destination. The project was built in python using snscraper packages, along with flask. The Front end was in native javascript, css, and html.

Challenges we ran into

As this was our first time doing a hackathon together or not, we found the small amount of time to be difficult to work with. Furthermore, the contents of the project we were working on were completely new to us, so we were learning as we went along which was -- while challenging -- rewarding at times.