Robinhood Controversy

Wordcloud based on top 2000 tweets about Robinhood using TweepyAPI

Background and requirements

Twitter has been buzzing with talk of Robinhood after they stopped allowing trade on certain stocks, I decided this was the perfect time to data mine through twitter and find out what most people had to say about Robinhood. I needed to create the code to obtain the tweets and find the top 2000 dealing with Robinhood. I also had to update the stop words to remove @ usernames and links.

Code

The code for the WordCloud can find in this GitHub post — The code for Robinhood Parse

Environment

• Python

• Jupyter Notebook

• WordCloud

• MatPlotLib

• numPY

Work with API

TweepyAPI

Conclusion

The top words in this cloud show exactly what's been all over my timeline, like AMC, GameStop, GME, WeBull. It surprised me that Dogecoin and Elon Musk aren't more frequent because I've seen those names quite often this week. I think it can be beneficial to look at trends this way, to get all the keywords and search them up alone to get a better understanding. For example, if you looked up Robinhood and keyword "lawsuit" it would tell you everything you need to know about the lawsuit posed on Robinhood because of the current situation.