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THE VIDEO SHELF · psychographic targeting

The Power of Big Data and Psychographics | 2016 Concordia Annual Summit

Alexander Nix of Cambridge Analytica presents at the 2016 Concordia Summit on using big data, psychographic profiling and behavioral microtargeting in elections.

Why HN readers recommended it

HN points to it as the company's own pitch, used in debates about data-driven manipulation and extrapolated to today's AI.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Concordia
Topic
psychographic targeting
Format
talk
Level
general
HN recommenders in dataset
4
HN mentions in dataset
10
Recommendation years in dataset
2017–2026

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • I urge everyone to watch this video from Cambridge Analytica about their techniques with big data and psychographic profiling leading up to the 2016 election. Very dystopian, it almost feels like a seminar with a Bond villain. Quote from the video: > "we were able …

    kbaker on Hacker News · 2018-03
    In Suspending Cambridge Analytica and SCL Group from Facebook
  • If you feel like the article is too long, you can watch this 11 minutes presentation: [VIDEO] . It summarizes their methodology. I took the presentation link from the article.

    cplanas on Hacker News · 2017-01
    In Trump Knows You Better Than You Know Yourself
  • The article [1] and video [2] below shed some light on the "how". The video is mentioned directly in the article. The text explains how highly sophisticated targeting was deployed by the Trump campaign, and how it differed from Clinton's campaign. Highly informative. [1] [LINK] …

    fmihaila on Hacker News · 2017-01
    In Make America Hate Again

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.