Setgo and LJMU Open Labs are hosting me to go to Liverpool & give a master class on Big Data, next week on Friday afternoon. Really looking forward to it. Come and join the fun, share your ideas with us, and pick up some new tips, too. http://bigdatamasterclass.eventbrite.com/
n.b. it’s in Liverpool
Interesting day at Facebook’s London Mobile Hack yesterday. Disclosure: I skipped the hack part, which was scheduled for 5pm to 9.30pm. But I attended a full day of lectures before I snuck off. So I hope I can wear the t-shirt without shame.
At one point I asked Simon Cross (who built the Graph Explorer) about the relationship between:
and
I wasn’t really sure why I was asking the question – I just had a nagging feeling I was missing something. I didn’t understand how custom actions, which are extensible, were related to activity permissions which were (presumably but not necessarily) defined in the same way (but not necessarily set to the same value) for every app.
In retrospect I was just confused. My thinking now is that there is no necessary relationship. The custom actions which are graph extensions occur as a combination of app design, Facebook approval, then, at run time, are instantiated and populated via user agency occurring via the app. These custom user actions doesn’t necessarily have any link to the FB app action permission schema, although they of course might have a link if the app action involved actually involves, at a more abstract level, any of the types of actions which occur in the permission schema. Ok well that’s sorted then. Maybe. Unless I’m actually wrong here, which of course I might be. In which case tell me.
Setting aside for the moment whatever ontological muddles I might have gotten into, the answer I got from Simon was, I think, much more interesting than the question I asked. What he said was that subject to the appropriate permissions having been granted by the user, it was possible for an app to read data stored in the user’s graph by other apps. He explained that this was because Facebook viewed all data as the user’s data, and it was, therefore, for the user to decide who could view it.
Here’s an example which I just fished out of the docset:
“If the user has granted your app with the user_games_activity permission then this api will give you scores for all apps for that user. Otherwise it will give you scores only for your app.” (source: https://developers.facebook.com/docs/reference/api/user/#friends accessed 13.34 GMT 6 March 2012)
This has a variety of interesting potential uses, which I am sure you are busy thinking about right this minute.
Of course – what’s sauce for the goose is sauce for the gander. If the user has granted permission, you can see the trail other apps have left, but other apps will be able see what YOU have salted away in the graph, too.
Facebook just performed surgery on itself, and nobody noticed.
Eytan Baksky, Itamar Rosenn, Cameron Marlow, and Lada Adamic recently produced an impressive display of heavy lifting in which they looked at information propagation patterns on the Facebook social graph (check out the summary here, and the full article here). Why ‘heavy lifting’? Well, their sample size was over 250 million, and each person’s NewsFeed was either dynamically altered or wasn’t, depending on which experimental treatment condition had been randomly assigned. Not only that, but each person’s sharing behaviour was assessed in detail, in relation to the sharing behaviour of each of their individual friends. We’re not just talking Big Data here. We’re talking Big Data with fries.
Putting aside for a moment from the actual questions the Facebook Data Team asked and the answers they got, both of which are interesting (so I will try to get to grips with them – in a later post), I think the most surprising thing about this study is the fact that Facebook publicly used itself as an experiment, and nobody blinked. What they did in the study was only a tiny, weensy bypass operation. (The experiment involved withholding some newsfeed items from its users that they would normally have seen as result of the operation of the service.) But it was surgery none the less.
My own private speculation is that Facebook experiments on itself all the time, and then quietly gets on with applying the lessons it learns by doing so. But the Data Team’s world-facing work is usually correlational and observational rather than directly experimental. So this work is different: here, they did tweak around with Facebook, and they did publish their results. And I am surprised that nobody seems to be interested in that fact. I don’t have an issue with the fact they did it. In fact, I’d be a bit disappointed if they didn’t. But then I’m an experimentalist by background.
Don’t get the wrong idea: I do care whether I see stuff that’s sent to me. When I get the post delivered from the postman each morning I don’t expect him to randomly hide some of it from me just to see what would happen. Interestingly I have heard more than one story in which it turns out that is just what (a few lone and deranged) postal workers sometimes actually do. But although this isn’t unheard of, at least as an urban myth, it’s not what I expect, and were the behaviour to be discovered, I would expect it to be stopped. Ignoring my post is my job, not my postman’s.
But my view of my Facebook Feed is different. My understanding of my Feed is that it is cooked up according to a secret sauce recipe which, although it isn’t exactly to my personal taste, represents Facebooks’ best efforts at optimising something of interest to it. And I believe the recipe for this sauce is constantly evolving, although the brand remains the same. So to find there has been a tiny systematic tweak made to it, whereby some information was hidden for some people when it would normally have been displayed, is neither a big shock, nor a bad one.
What surprises me about it is that it seems to have been so generally unsurprising. I have a few different theories about this:
The Lean Startup ideas of Eric Reis have become so pervasive and “baked into the DNA” of our culture that everyone who thinks about the matter expects to become part of some massive multivariate test whenever they encounter any application or platform.
Nobody who would potentially have been offended or puzzled by having their NewsFeed tweaked around with actually understood what was happening.
Here are some screenshots I took this morning about the relative numbers of people who publicly lauded the research summary, versus the full research article.
The score is as follows. There were over 5,000 social actions performed on the summary. And 165 on the article itself.
The change made was so non-material in its potential and actual impact that nobody in their right minds could possibly make a big deal of it.
So, no shortage of theories. But I’ve no idea which one is right. Do you? My guess about the recipe is: 20% Theory 1, 60% Theory 2, and 20% Theory 3.
The highly munchable and crunchable soundbite about the study, distributed with the summary , was that the research demonstrates that Facebook is not an echo chamber. This meme has bounced around languidly, albeit dominantly, following the release of the research. I believe that the research, while interesting, does not actually warrant this conclusion directly. But what the research does demonstrate, by its very existence, is that whether or not Facebook is or is not an echo chamber, for sure it sometimes acts like a hall of mirrors.
Source: ItDan - Flickr
