Twitter's graph (2012)
dcurt.is
dcurt.is
So, clearly this is from 2012 and the thesis is 100% incorrect (in fact, pretty much inverted). The interesting thing is that this is pretty much how the general populous still thinks Facebook does it's ad targeting. The author massively overlooked machine learning. I don't have first hand evidence, but I can only guess that Facebook is crawling every piece of data possible (pictures, messages, etc) and then draws conclusions of my interests there. In addition to this, all FB user info is being hashed and compared against consumer spending data (e.g. DLX and Acxiom).
The level at which FB and Google can target us is staggering. There is a reason these companies make so much money.
I'm so glad I deleted my facebook account years ago for this fact alone. I don't need to give all my information for free to facebook to use what is essentially IM.
Machine learning can only do so much. Human editing will always win over machine algorithms, and Twitter users curate their follows. Also, machine learning only improves conversion rates by 2x. Meanwhile, I've seen a 10x conversion rate improvement when hand editing ads on a site. Machine learning ads are why you have out-of-context ads that destroy a sites user experience.
Source? Genuinely curious, about to kick off a campaign on Twitter in an esoteric area (triathlon) and can't imagine it will be a higher ROI than FB.
> Also, machine learning only improves conversion rates by 2x. Meanwhile, I've seen a 10x conversion rate improvement when hand editing ads on a site.
I'm not sure you're following my line of reasoning here (or maybe I'm not following yours). The machine learning becomes useful when I try to target people's behaviors. For example, I say "Facebook I want to run an ad against all people who actively run and get them to buy running shoes". Facebook is going to optimize to serve up ads to people who (1) run (determined by messages they send to people "hey great run, I did 5km last week" or integrations with RunKeeper, Strava, etc, or maybe I have pictures of me running a race) (2) click ads (easy enough) and (3) will purchase online (determined by conversion pixels of previous campaigns). This is a gross oversimplification of course.
> the thesis is 100% incorrect
and guessing that:
> Facebook is crawling every piece of data possible (pictures, messages, etc) and then draws conclusions of my interests there. In addition to this, all FB user info is being hashed and compared against consumer spending data
That's a pretty sweeping statement. You'd be surprised at how naive (and distinctly not-amazing) the machine learning algorithms used in-production at places like Facebook can be (in-production, as opposed to cool research papers that aren't actually used in-production).
Going off of your simplified example, there are tons of contexts in which someone might say "run" without meaning anything related to the athletic activity. That's the definition of shitty targeting (false positive).
If that means Facebook & Google have more room for future optimization, awesome... but I fear they really make money off sheer volume of ad inventory. Watch the Facebook ads and how they refresh every couple of minutes - that isn't about extra targeting or clever machine learning, that's just extra inventory of ads charged per impression.
This doesn't seem to be true. It's true of real platform plays, like a desktop or mobile OS.
There are cases where the relationship is important, like in the early stages of a product - where in some scenarios you need both. And yes, if you need developers, and developing for platform x is hard, and y is easy - all else being equal y would win.
There can't be more than 50,000 devs who used the Twitter API. I definitely don't think they're going to be the deciding factor.
That being said,I would never use the Twitter API based on the horror stories I've heard.
Did this article imply that App.net was about to kill Twitter since App.net was open?
Heh.
I don't know if App.net could have ever killed Twitter, but Twitter closing made it harder for users to transition to App.net in the first place.
Isn't that completely the same or isn't Facebook even better in that respect, because Facebook pages are much more often real interests, whereas Twitter users that are followed are more often people instead of interests?
If friending disappeared, Facebook would cease to exist as a product. If liking disappeared, a huge chunk of activity (40+%?) would disappear. If following disappeared (you could still friend or like), I don't think many people would notice.
That wasn't my contention - your contention was:
> Following is not "a thing" that's popular to do on Facebook.
And yet, the hundreds of millions of people who have followed brands on Facebook would indicate that it is popular. It can be popular without being "the nexus".
How did this happen? I've been using Twitter API these past years but I'm not aware of this "friend finder" feature. Getting friends/followers is still there in the REST API.