Rather than tweetstorm, one post with some reactions to the people recommendation tutorial at #recsys2016 by Ido Guy (Yahoo Research, Israel) and Luiz Pizzato (Commonwealth Bank of Australia, Australia), primarily Luiz’ part.
Not sure people recommendation has to be symmetrical; it would be interesting to ponder use cases where that’s not true (Twitter is the one that comes first to mind).
The point that success often gets measured outside the system is a good one — the example of a dating site being successful when people stop using it because they matched was cute. Victoria Sosik, Steve Ibara, and Lindsay Reynolds thought about that in persuasive systems, and the Suhonen et al. Kassi system in barter and social exchange systems.
Random side thought: wonder about designing not just a dating site but a relationship one, where you might use the site to help continue and develop the relationship long term. Doug Zytko was thinking about this a while ago.
Claim that successful people recommendations are ones that lead to interaction is a little overstated maybe. For instance, one potential benefit of “unsuccessful” recs that don’t lead to interaction is learning more about the space of possible people — what is this social circle or company or population of mates _like_?
Point that unsuccessful people recommendations can have psychological effects was nice, as was the idea that people might be more inclined to be makers or receivers of people recommendations, and that varies by context…
The point that people might become less picky over time if early attempts on dates, jobs, etc. don’t pay off (or more picky if you have much success) was interesting, but is that algorithm-actionable? Or is that more about how far people are willing to go down a list of recommendations?
Fraud concern feels a little overstated, even with the legitimate threats of fudgers, liars, scammers… Reminds me a little of the obligatory preventing collusion section in crowdsourcing papers.