aandon

I've been using them in SF and it's a nice perk to not have to worry about filling up. The bigger perk is just having someone more diligent than myself checking all the stuff I let get too far: wipers, tire treads, headlights, etc

aaaaaaand it's not on the App Store

Agreed, the best thing you can do is Google "_____ product review" and look for credible reviewers, someone with a reputation to protect. I worked with a product company where v1 had some product flaws and started receiving negative reviews, but it was very easy to overwhelm those with fake positive reviews across the web. Then when we came out with a much better v2, we got a scientist in our field with some following to do a short positive video review. That is difficult to get (I'm not talking about YouTube/Instagram/mommy blogger reviewers who give positive reviews to anyone who will send them free product) and there's no way he would have put his name on the line unless he had tried out the product on his own extensively. Any product company worth its salt should know this and get a few of these expert reviews posted to the web.

Indeed I know it's a close-knit community. Most of our 20-person team came from anti-fraud teams at Google. I'm guessing the "silliness" you're referring to is the talk of Facebook not being incentivized to block spammers. I think kbenson articulated best what I was trying to say, that there are tradeoffs in blocking good users and decreasing apparent user volume when fighting fraud. Facebook would obviously not be wise to catch every single fraudster because there would be a high number of false positives, so a balance must be struck. As I'm sure you know, fraud teams at many companies often clash with the marketing team because they're protecting the bottom line (sometimes at the expense of the top line) respectively, and vice versa.

> The incentive to make fake accounts on Facebook is orders of magnitude greater than almost any other social network.

Not true. In the article, the writer pays Russell $15 for 1,000 likes. Being generous and assuming each of Russell's fake accounts can farm out 100 fake likes, he's making $1.50 per fake account before it gets shut down. Compare that to social networks where you can directly extract payments from other members by listing fake items for sale, laundering payments from fake credit cards (on other fake profiles) to yourself, or link-baiting other users. A single successful fake account on those networks can easily net you $100.

> Facebook has methods that radically exceed this method in both complexity, precision, and recall.

Agreed, and indeed Simility's models have much more complex methods too, but a) I wanted to post an interesting example everyone here would understand and b) I still say Facebook is not using anywhere near its full ability to stop these fake profiles given how rampant this fraud scheme is on their platform. (Again, follow the money, FB has very little incentive to stop these fraudsters who are only inflating their own numbers. It's important to keep them in check, but there's no incentive to waste resources stopping them.)

Product manager at fraud detection company Simility here. I'm very surprised Facebook hasn't put more effort into curbing fake accounts, makes me think it's very low priority for them. We have social network customers who are much smaller than FB, yet have gotten their fake account rates far below FB's.

One effective strategy we've employed not mentioned here is category mapping: if an account of type A, only targets accounts of type B for likes (especially if they ignore categories C, D, etc.), this is usually a high indicator of fraud. For example, one very common strategy is to create a fake account for an attractive female to friend many male accounts (especially relatively new accounts unaware of these tactic). This can be easily detected by analyzing the gender and account age of all targets and coming up with a diversity score. Low diversity score = likely fraudster.

Normally an order on your back-end is linked to our device ID with a session ID. However our device ID can also accept user-generated data within fields on your website/mobile app. So if your customers enter their email address during your checkout process, that email will be tied to device ID and you can then look up suspicious orders by their email address.

Google Sketchup is an unsophisticated but good quick-and-dirty modeling app. It wouldn't be a huge leap to see it built in a CSS framework like this.

The professionalization of the peer-to-peer space is getting incredibly interesting. Hotels must be realizing that hosts are starting to offer places that are essentially like hotels... only with much more diversity, many more locations, more unique features. Tools like this are definitely driving some interesting changes in the space.

Interesting idea, this is the first virtual hackathon I've ever seen. Wonder if this is the first time someone's ever tried this. Could be huge