This github repo contains the code I used to perform the hypotheses tests for my Twitter portfolio project.
Problem: Negative Twitter experiences can affect the platform's retention and user growth rate. I aimed to understand people's Twitter experiences to improve these metrics. Twitter's growth rate for 2022 is 2% while its current global retention rate is 84.1%.
Approach: I ran a survey for ten days and explored the data with Excel, Python and a bit of R.
Insight: I found that 73% of my sample use Twitter for news, 37% for trends and comedy and 28% for networking. Likewise, the quality of twitter’s content affects how people feel about Twitter and the amount of control they have over Twitter affects how they use the platform.
Impact: I recommended optimising Twitter for news, networking and trends and granting people more flexibility to control their Twitter feeds beyond the available options. If Twitter does this, it’ll improve its global retention and user growth rate.
- Case Study: https://funmilayoobasa.com/2022/03/07/improving-twitters-retention-user-growth-rate/
- Explanation of Insights (Testing my Twitter Bias): https://funmilayoobasa.com/2022/09/07/testing-my-twitter-bias/