1. Big Data Psychology
Michal Kosinski mk583@cam.ac.uk
Image source: Facebook

2. Cambridge University
Psychometrics Centre
• 30 years of experience in psychological
assessment
• Strategic Network of Cambridge University =
expertise in wide variety of disciplines

5. DIGITAL FOOTPRINT
Also:
• Email / texts
• Verbal conversations
• Physical movement data
• Credit card records
• …

7. Get some data
related to an
individual
(purchase history,
Facebook profile, tweets,
email, web browsing
history)
Translate it to
Facebook
Graph ID
(Oreo =
114998944652)
Send it to
ApplyMagicSauce
API
Get a detailed
psychodemographic
profile

9. How accurate is digital profiling?

10. Validation study:
1. 60.000 US Facebook users
2. Detailed psycho-demographic profiles
3. Tested the accuracy of predictive models
Kosinski, M., Stillwell, D.J., Graepel, T. (2013) Private traits and attributes are predictable from digital records of human
behavior. Proceedings of the National Academy of Sciences (PNAS).

11. Prediction Accuracy: Numeric Variables

12. Only Facebook Likes?
(Other digital footprints are even more informative)

13. Applications in marketing

14. Detailed psychological profiles of each
and every consumer
(both in online and offline environment)

15. Psychological profiles of groups
(customers/fans/audience/readers/etc)

16. Openness
Conservative &
traditional
Liberal &
artistic
Conscientiousness
Spontaneous &
impulsive
Well organized &
hard working
Extraversion
Contemplative &
happy with own company
Agreeableness
Competitive &
Working alone
Team working &
trusting
Neuroticism
Competitive &
Working alone
Laid back &
relaxed
Engaged with outside world

17. Openness
Conservative &
traditional
Liberal &
artistic
Conscientiousness
Spontaneous &
impulsive
Well organized &
hard working
Extraversion
Contemplative &
happy with own company
Agreeableness
Competitive &
Working alone
Team working &
trusting
Neuroticism
Competitive &
Working alone
Laid back &
relaxed
Intelligence
Low
Engaged with outside world
High

18. Target anonymous users using
psychological profiles

19. Extraverted &
open to experience
Well organized &
competitive
Cooperative &
happy
High IQ

20. Build your own predictive models

21. Adjust your offer and language on the
individual & group level

22. Agency and Communion on Facebook: An Open Vocabulary Analysis of Gender (submitted) Gregory Park, H. Andrew
Schwartz, Margaret L. Kern, Johannes C. Eichstaedt, Adam M. Croom, Lyle H. Ungar, Martin E. P. Seligman, Michal Kosinski,
David Stillwell

24. Language used

25. Language used

26. Language used

27. Language used

28. Language used

29. RISKS
•
•
•
•
Digital withdrawal
Fake footprints
Legal issues
Creepy targeting

30. Thank You!
mk583@cam.ac.uk
Michal Kosinski
Cambridge University