Preliminary Investigation on User Interaction with IBM Watson Analytics
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FT articles: Bank hiring: Wall St turns to machines to find better-behaved bankers & Making the grade at Deutsche Bank
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PAPER Predicting personality traits related to consumer behavior using SNS analysis
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biased ARTICLE and PAPER: "Here's how to read someone's personality by their online profile picture"
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PAPER The Gamification User Types Hexad Scale
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article: Predictive Analytics, Big Data, and How to Make Them Work for You
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IBM will analyze Twitter data and turn it into something actionable for the enterprise.
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IBM Deciphers Personality Types From 200 Tweets ?
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PAPER System U: Automatically Deriving Personality Traits from Social Media for People Recommendation
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Unfortunately the Big Five normative personality test is obsolete, it has been proven as an incomplete and incorrect model of personality. The HEXACO (a.k.a. Big Six) is another oversimplification.
Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)
That is the only way to improve recommender systems, to include the personality traits of their users. They need to calculate personality similarity between users but there are different formulas to calculate similarity.
In case you did not notice, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates!!! because they mostly use the Big 5 to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old.
Online Dating sites OFFERING COMPATIBILITY MATCHING METHODS BASED ON PERSONALITY SIMILARITY have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 normative personality test instead.
The same applies for Personality Based Recommender Systems.
Very easy to copycat eHarmony, but very difficult to innovate: a 100 times better algorithm than eHarmony.
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