The document discusses using machine learning to analyze social media data and its relationship to performance metrics in the NBA. It first shows an example of increased engagement for a celebrity athlete over time on social media. It then discusses using social media signals to predict metrics like pageviews. The document explores what social media can predict about NBA teams and players, like team valuation, player performance, attendance, endorsements, and salary. It analyzes the relationship between these metrics and concludes some players should focus on scoring over team play to earn higher salaries, and that fan social engagement better reflects true performance than salary.

1. Social Power and Influence In The NBA
Noah Gift
Professor UC Davis GSM: Machine Learning, Computing
Founder: Pragmatic AI Labs
Author

2. Brett Favre Breaks Our Internet
==+
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3. Social Media Has Hidden Power
Could we use Machine Learning to play Social Media
Moneyball?...Yes we can…
Conor McGregor July, 2014
58 Retweets
146 Likes
Conor McGregor March, 2018
3,228 Retweets
23,601 Likes
16,000 % Increase in
Engagement over 4 Years
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4. New Contributors Feed into ML Social Power Feedback Loop
Find Social
Handles
Find Signals
to Predict
Pageviews
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5. Takeaways From Experience
 There are lot of hidden power in Social
Network signals
 Possible to grow a platform without buying
any traditional advertising
 Who really has the power…celebrities or
social platforms…cracks are emerging?
 More to discover….
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6. Network News
Editor/Engineer
Lead Systems
Administrator Lead Editorial
Engineer Python Developer
Lead Python
Developer
Director
Engineering CTO & GM Consultant
School & Work
Full-time
Worked on
Avatar Movie
Wrote Best Selling
OS X App
Wrote O’Reilly
Book on Python
School & Work
Full-time
Pearson
Book on AI

7. What Can Social Media Predict about the NBA?
 True Valuation of NBA Teams?
 True Player Performance?
 Attendance at games?
 Endorsement deals?
 Player Salary?
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8. Collecting Data Sources is Always Painful
Arena Attendance
Local Engagement & Willingness
to Pay
Social Power,
Influence and
Performance NBA
Global Popularity Global Engagement & Influence
NBA Datasets
On The Court Performance
Salary
Pay for Performance
Census Data
Population Density & Real
Estate Values
Endorsements
Brand Value
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9. NBA Teams
 True Valuation of NBA Teams?
 True Player Performance?
 Attendance at games?
 Endorsement deals?
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10. Biggest Drivers of NBA Team Valuation?
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11. Three Types of NBA Teams
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12. Team Valuation Conclusions
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13. What About NBA Players?
 Are fans or owners better able to
recognize talent?
 If a player wants to make the
highest salary, do they focus on
their team or scoring?
 What is the relationship between
social media and endorsements?
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14. NBA Player Social Power and Performance
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15. Points/Game Predicts NBA Salary
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16. Do NBA Fans Value Team Play Over Points?
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17. What about NBA Endorsements?
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18. NBA Player Conclusions
 If players want to make the most money in Salary, they
should switch to teams that let them score
 Many NBA Players Don’t Have Social Media Handles
 Fan Social Engagement is a better predictor of true
performance metrics than salary (Smarter than owners).
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19. Questions?
 How to learn more about Social Power in the NBA
- Connect on LinkedIn
- Read IBM Developerworks Article
- Fork my social power on Kaggle
- Buy my book on Pragmatic AI
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