A pleb on the web tries to understand psychographic targeting

Transcript

1. Psychographic targeting
   Siva Swaminathan
   

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3. Background
   

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4. How and why did this talk come about?
   

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5. Diffusion of innovation
   Essentially, an analysis of sociology (individuals and social links).
   Very broadly applicable, for the spread of all kinds of ideas
   (fundamentally what makes us human?)
   

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6. Legibilizing social interactions
   Electronic social networks which make up fabric of the web, are
   excellent for providing a legible map of sociography,
   allowing for surgical dexterity in targeted messaging.
   

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7. What spreads effectively need not be
   innovation or even truth
   Reproduction, Variability, Heritability, Differential selection
   (Just needs a good fit into incidental constellation of environmental factors)
   (see arguments by Daniel Dennett, Bret Weinstein)
   

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8. Methodological individualism
   (factorizable structure of mathematical models)
   Person is described by their interests
   Person is described by their psychography
   Person is described by their sociography
   

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9. The marketing game
   

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10. "Half our marketing budget is wasted …
    but we don't know which half!"
    

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11. Tracing back to Edward Bernays (1928, 'Propaganda'),
    a close relationship between marketing and psychology.
    (Adam Curtis, 'The century of the self')
    

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12. Innovation diffusion models
    Segment individuals into each stage of adoption
    Innovators, Early Adopters, Early majority, Late majority, Laggards
    Mapping between identifiable/targetable traits & segmentation
    

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13. Market segmentation & user profiles
    Typically industry/context-specific analysis, sponsored by
    market leaders, or trade associations, or consulting agencies.
    eg:
    Only broad targeting (typically mass media)
    "Subarus for lesbians"
    

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14. Structured models arbitrary tidbits
    Sub/urban lifestyle choices?
    Preferred car models?
    Which OS & browser?
    Thermostat prefetences?
    etc.
    ≫≫
    

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15. Personalization: automated, and at scale
    "Direct marketing" (Lester Wunderman, 1960s)
    Convivial Industrial
    ⟶
    

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16. The technical aspects of
    inferring profiles
    

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17. Collaborative filtering
    N users, B behaviors Humongous sparse matrix
    Eg: Product recommendations, Ad effectiveness, Topic modeling, etc.
    ⟹ N × B
    

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18. Low-rank approximations
    Simple algorithms, eg: SVD, NNMF, LDA
    [N × B] ≈ [N × r] ⋅ [r × B]
    

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19. "Big (wide) data, with simple algorithms
    beats complicated models"
    Humans are not unique snowflakes,
    but well approximated into a handful of types
    

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20. From how we behave to who we are
    Could we generalize across domains?
    What might be a more intrinsic characterization of people?
    

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21. Big-5 (OCEAN) model
    Openness, Conscientousness, Extraversion, Agreeableness, Neuroticism
    (rank-5 approximation, SOTA psychology reasearch)
    

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22. Vacuuming up digital exhaust
    responses in silly quizzes
    links you click on
    time spent on various pages
    location tracking (bluetooth, GPS)
    Facial recognition and body trajectory
    Eyeball tracking
    etc. behaviors
    

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23. Experiment summary
    

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24. Models easily beat closest confindants!
    

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25. More "factors"
    Demographics [who] (eg: age, gender, location, etc)
    Psychographics [why]
    Personality traits: (eg: OCEAN, thriftiness, risk aversion, etc.)
    Psychological states: (eg: mood, emotions, stress level, etc.)
    less temporally stable, but more effective?
    Other factors: Behavioral data [how] & Transactional data [what]
    

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26. Using inferred profiles
    

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27. Targeting by psychographics (1)
    

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28. Targeting by psychographics (2)
    

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29. "A/B testing"
    Counterfactuals, not just correlations
    

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30. Other modalities of influence
    Which voice would have the desired influence?
    What wording would have the desired influence?
    Target messages for virality?
    

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31. GPT3, and automated (personalized)
    content generation
    Eg: Adolos Substack GPT-3 autogenerated
    

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32. Same methods for political messaging
    Psychometric Profiling: Persuasion by Personality in Elections (link)
    

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33. Exploring consequences
    

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34. Possible beneficial uses of
    personalization
    Mental health diagnosis and interventions
    Better matching (employment, dating, entertainment, etc)
    "Nudge" towards healthier outcomes
    Custom insurance premiums and interest rates
    

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35. Uncomfortable examples
    Target pregnancy
    Uber "rides of glory"
    Large scale emotion manipulation study on Facebook
    

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36. Fundamentally breaks common
    knowledge
    (eg: Say's law of one price)
    Discrimination (eg: "good" and "bad" price discrimination)
    

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37. Psyops: Disinformation & Nonlinear war
    Mess with sense-making apparatus
    Spread FUD (war, elections, political polarization, etc)
    Correlate power usage to bring down the power grid!
    "Global village" (McLuhan, 1950s)
    (BLM protests in BLR and NZ, ignoring COVID lockdown!)
    Gerasimov doctrine
    

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38. Assault on individual agency?
    At what point should we regulate
    targeted messaging like the Imperius Curse?
    (ambient nudges better -vs- direct control)
    Why is advertizing different from rape?
    (Memetics -vs- Genetics)
    

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39. Thank you
    

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40. // reveal.js plugins
    

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