The Facebook Algorithm Mom Problem • Hacker News Board

Re: The Facebook Algorithm Mom Problem

#221

Post by rhizome » Wed, Jul 12, 2017, 10:54 PM UTC

icebraining wrote: post #211

rhizome wrote: post #188

Earlier quoted context omitted.

Because if e.g. you watch a Tool video, the ad rates for you watching a Korn video after that are higher than if you watch a Zeni Geva one. Alternatively, Kesha > Lady Gaga vs. Kesha > Joni James. Unscientific, but it comports with conventional wisdom with regard to fiduciary duties to stockholders.

Because if e.g. you watch a Tool video, the ad rates for you watching a Korn video after that are higher than if you watch a Zeni Geva one But why? If I've watched hundreds of Zeni Geva videos over the years, but it's my fifth Tool video, why would I be more likely to click on a ad on a Korn video?

It's not that they think you'll be more likely, it's that they rather you did, so the suggestion emerges. Recommendation engines are a funnel for revenue.

Re: The Facebook Algorithm Mom Problem

#222

Post by sgustard » Wed, Jul 12, 2017, 10:58 PM UTC

unoti wrote: post #206

Semaphor wrote: post #101

Earlier quoted context omitted.

I'm not sure if it is because of weird tastes or something else. But for sites like Steam, YT, Netflix I always wish for more tuning parameters because their recommendations are all horrible. On Netflix, for example, I get recommended stuff that's similar to other things I didn't like. Amazon is often the best of them for books because their engine seems to only really value the last few things I looked at / bought a…

> for sites like Steam, YT, Netflix I always wish for more tuning parameters because their recommendations are all horrible. The problem with those recommendation engines is that they're not optimized to serve your needs. They're optimized to serve the goals of their respective companies. And the problem comes when your needs are a little incompatible with the needs of the company. Consider Netflix for example. Their…

Netflix has a tiny catalog, so investing in making recommendations from that tiny catalog is mostly wasted. Half of Netflix's business now is House of Cards, so their entire algorithm consists of recommending House of Cards to people who haven't watched it yet, and random content to the others.

Re: The Facebook Algorithm Mom Problem

#223

Post by rhizome » Wed, Jul 12, 2017, 11:02 PM UTC

icebraining wrote: post #207

quadrangle wrote: post #160

Earlier quoted context omitted.

Because they aren't trying to help you enjoy videos over the long-term, they're trying to keep you from going over to Facebook where their addictive algorithm will take over and reduce your likelihood of returning to YouTube! It's a classic race-to-the-bottom. If YouTube lets Facebook keep you addicted, you won't get to the long-term. http://timewellspent.io/ is good for perspective

Yes, but that has an unspoken assumption that recent habits are more additive than longer term ones. I find that suspect; after all, you've already shown that you'll go back again and again to these kinds of videos, whereas you might spend a couple of hours watching a bunch of videos of a kind that you'll never be interested in again. Personally, I find YouTube terrible at keeping me engaged. Even when I want to keep…

Yes, but that has an unspoken assumption that recent habits are more additive than longer term ones

This is too fine a point. A user will "select" a default choice by doing nothing, and it's in YT's interests to provide default choices that reward the company. This has been researched for decades and is supported by, among other things: https://en.wikipedia.org/wiki/Status_quo_bias

Re: The Facebook Algorithm Mom Problem

#224

Post by revmoo » Wed, Jul 12, 2017, 11:04 PM UTC

c3534l wrote: post #216

ryanbrunner wrote: post #95

I find a lot of sites feel like they're overtuning their recommendation engines, to the detriment of using the site. YouTube is particularly bad for this - given the years of history and somewhat regular viewing of the site, I feel like it should have a relatively good idea of what I'm interested in. Instead, the YouTube homepage seems myopically focused on the last 5-10 videos I watched.

Part of that trend is because recommendation algorithms aren't all that interested in making recommendations anymore. They're interested in getting sales or views. To do this, they use dumber algorithms that are easier to understand ("people who bought this also bought...") and over-value recency. They're not helping you find new content, they're trying to prolong the time you're on youtube.

I have been paid to write an algorithm like this. It matched you to relevant content, but then a manually configured weighting table would skew results to more popular sources. It went as far as taking into account the number of leads we had sent each partner that month as a percentage of their quota

Re: The Facebook Algorithm Mom Problem

#225

Post by Nition » Wed, Jul 12, 2017, 11:06 PM UTC

compiler-guy wrote: post #105

For every social media site XX: Question: "Why does XX do things this way?" Answer: "Because it increases engagement." Why does the Facebook algorithm do this? Because it increases clicks. Why does Youtube use autoplay? Because it increases watch time. For every single social media site.

This article is about how while Facebook's intention is to increase engagement, it backfires in this specific case because the algorithm takes his mother's Like and interprets that as "this post will get the most engagement from family" when actually it was more targeted to outsiders.

Re: The Facebook Algorithm Mom Problem

#226

Post by emodendroket » Wed, Jul 12, 2017, 11:13 PM UTC

scottmf wrote: post #185

emodendroket wrote: post #52

Earlier quoted context omitted.

Well, that would seem to be contradicted by the observation that his friends do engage with them if he hides the posts from his mom.

I feel like accounting for people who like everything would be one of the first things built into such an algorithm. He should try alternating the privacy settings with each post.

I realize there isn't an extreme level of rigor here, but it gets tiresome reading HN comments where it's just a series of increasingly extravagant hoops for the original article to jump through before the commenter is willing to accept that the findings might be valid and give any consideration to the article's implications.

Re: The Facebook Algorithm Mom Problem

#227

Post by icantdrive55 » Wed, Jul 12, 2017, 11:14 PM UTC

fletchowns wrote: post #204

afarrell wrote: post #201

Earlier quoted context omitted.

The fact that Amazon doesn't have a way to recommend complimentary products ("oh, you just bought a tent? You probably want some bug spray") boggles.

Isn't that what the "frequently bought together" suggestions are?

And that algorithm works.

I once bought an obscure heli-coil. It knew to recommend the right bushings, and right pitched screws. It knew I would problally need the extra stuff. The price was low enough to chance it.

Traditional retail needs to up their game.

That said, I refuse to pay for Prime. Why--I just bought too much unneeded stuff.

I'm currently trying to only spend on what I really need. Including spending a lot to impress pretty women. I figured if they are impressed with seemingly fancy chit; I don't need it. Or, we'll spend your money? I'm quite the guy? I wasen't born this way, just evolved? And every man knows when to pull out the equal card? At an overpriced dinner? Never again. How did I get on this tangent?

Re: The Facebook Algorithm Mom Problem

#228

Post by [deleted] » Wed, Jul 12, 2017, 11:19 PM UTC

tgb wrote: post #209

inopinatus wrote: post #205

Earlier quoted context omitted.

To give some justice to the algorithm, after purchasing my first Dyson I wanted to replace all my vacuum cleaners with Dysen.

How many vacuum cleaners do you have?

[deleted]

Re: The Facebook Algorithm Mom Problem

#229

Post by dghughes » Wed, Jul 12, 2017, 11:20 PM UTC

kromem wrote: post #171

Facebook also has a serious problem in that its news feed is a content recommendation engine with only positive reinforcement but no negative reinforcement. So you end up with a ton of false positives even when actively interacting with the content, and their system doesn't even know how wrong it is. And should you really not like some content, the solution is unfriending the poster, rather than simply matching again…

That's like YouTube lord help you if you click on a video you don't like by mistake you'll never see the end of it in the recommended section.

It's to the point now where I just log out so I can see what's available rather than a continuous feedback of what I already watched.

Re: The Facebook Algorithm Mom Problem

#230

Post by samatman » Wed, Jul 12, 2017, 11:34 PM UTC

ThrustVectoring wrote: post #103

ryanbrunner wrote: post #95

I find a lot of sites feel like they're overtuning their recommendation engines, to the detriment of using the site. YouTube is particularly bad for this - given the years of history and somewhat regular viewing of the site, I feel like it should have a relatively good idea of what I'm interested in. Instead, the YouTube homepage seems myopically focused on the last 5-10 videos I watched.

Youtube is definitely over-weighing the last few videos. Then again, it's likely optimized for a different market segment. Especially with how many children are given tablets. Like, brief intense fascination with many subjects in general is genuinely hard to optimize for, especially when a huge portion of your market has long-lasting intense fascination with a few subjects.

This is often the behavior I want. I frequently queue up a song on YouTube and then let it keep auto-playing, if I hit one I don't care for I usually select off the sidebar of recommendations.

This only works because YouTube stays focused on what you're doing without trying to build a bigger picture of who you are. It would be nice if it could somehow do both, but I don't have a clear picture of how that UI would function.