About "The social power of algorithms"

The social power of algorithms

The recent TV drama Casual (2016) introduced the viewer to Alex, a disenchanted internet entrepreneur who obsesses over his algorithm. Alex’s algorithm, we discover, is the key to the significant success of his online dating company Snooger. He already lives an apparently limitless if unfulfilling life of decadence and luxury. Yet, he keeps tweaking and playing with the algorithm, trying to perfect it, trying to hone and refine its powers. Alex, it would seem, wants the algorithm to perfectly match couples and to predict successful partnerships – including for himself. With a nagging need to hone, he keeps fiddling and working at the algorithm to try to perfect the outcomes. He knows how to play the algorithm to his advantage, as do other users of the site. They know what combination of profile
features will produce lots of matches, but Alex wants the algorithm to match profiles in ways that cannot be played. When we return in the second season of Casual, we find that Alex’s co-directed company is now in trouble. The problem, we discover from the venture capitalists who wish to purchase the company, is that the algorithm is just too good. Its predictions are too precise. As a result, people are finding long-term matches and no longer need the site. The answer – to make the algorithm less predictive.
"The Match team is working on artificial intelligence and its matching algorithms."???
Synapse: the Match algorithm? 
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/07/match-groups-mtch-ceo-on-q2-2016.html

 
PAPER A Preference-Driven Database Approach to Reciprocal User Recommendations in Online Social Networks
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/08/paper-preference-driven-database.html

PAPER: Tensor Methods and Recommender Systems
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/03/paper-tensor-methods-and-recommender.html

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.


Which is the RIGHT approach to innovate in the Personality Based Recommender Systems Arena?

The same approach to innovate in the Online Dating Industry == 16PF5 test or similar to assess personality traits and a new method to calculate similarity between quantized patterns.  


The key to long-lasting romance is STRICT PERSONALITY SIMILARITY and not "meet other people with similar interests". 

Lack Of Innovation & Decadence can summarize the Online Dating Industry.
The Secret Sauce Behind Online Dating ? There is no one yet!
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/07/the-secret-sauce-behind-online-dating.html

The Online Dating Industry does not need a 10% improvement, a 50% improvement or a 100% improvement. It does need "a 100 times better improvement"

 All other proposals are NOISE and perform as placebo.