Episode 72: The Social Media Hacker's Guide to Better Data Science

Social media algorithms silently shape what billions of people see and how they interact online. While most data scientists work to optimize business value within platform rules, there's valuable knowledge to be gained from understanding how these systems can be exploited - knowledge that can make ethical data scientists better at their jobs.

In this episode, Tim O'Hearn joins Dr. Genevieve Hayes to share insights from his experience manipulating social media platforms, revealing what ethical data scientists can learn from understanding the dark side of algorithmic systems.

This conversation reveals:

1. How social media platforms are essentially just sophisticated recommendation engines [08:16]
2. The "canary" technique for detecting when underlying systems have changed [11:36]
3. Why customer accounts often provide better testing data than artificial test accounts [13:56]
4. The importance of time series data collection for identifying suspicious patterns, effectiveness of campaigns, and understanding platform dynamics [18:04]

Guest Bio

Tim O’Hearn is a software engineer who spent years gaining millions of followers for clients by circumventing anti-botting measures on social networks. He is also the author of the new book, Framed: A Villain’s Perspective on Social Media.

Links

• Tim's Website
• Connect with Tim on LinkedIn
• Subscribe to Tim's newsletter
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE