What inspired us

  • Social media has a lot of conversation going and it is rare that we find anything on twitter that directly tells us an actionable way to get involved in that issue
  • Social media raises awareness and we wanted to use that awareness and make it more socially beneficial

What we learned

  • We learned that it is not easy to analyze social media data and filter it out to create something that will find tweets that could help raise awareness.
  • We learned more about natural language processing and how it's useful in a project like this
  • We also learned about creating twitter bots.

How we built it

  • Gathers twitter trends and uses natural language processing(via the vader package) to see peoples feeling towards a trend
  • Naively isolates keywords from tweets for retrieving charity data
  • Naively searches for charities and other information related to trend
  • A twitter bot provides people with links previously gathered
  • The Flask app does some visualization and displays bots tweets

Challenges

  • There won't always be trending topics that require attention so thats why we have a test case text file
  • The search for charities is still naive and needs to be improved before completely deploying the bot
  • Tweets in foreign languages causes gaps in data
  • We use limited data to make it usable for the hackathon, more optimization and more data will be needed for later.
  • The bot was not completely finished as we wanted to make it reply to popular tweets
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