Nice article in The Atlantic on recommendation algorithms and those that rely less on social endorsement than automatic other things. The important thing is the bias that systems always exhibit, and that we treat these as black boxes. (I described our approach to our learning as a black box in the first lecture, same idea.)
Month: October 2013
More Symposium Take Aways
David D on the Facebook hack, Kevin Bacon, why not become a hub, and that you need to do it. (Related to that thanks to Boglarka for this gem.) Denham on the Facebook hack, making, and the new world order. Boglarka concerned about sitting in a sea of media signals. Ditte using Castells (one of the key writers on the internet as an information economy come technological ecology) to think about technical come cultural determinism. Kevin on, well, Kevin, Facebook, and listening to your writing talking back to you. Lauren wants to keep technology under control. Jackie on creative freedom (I think creativity is defined and enabled by constraint, not the other way round, and while the sic-fi example might not have worked the question I think is who can you make something that is outside of ‘codes’?) Louisa has long bullet point list. Danielle has a good culled set of observations. Rebecca on whether technology controls or not (I don’t think it is about control, control assumes direction, a centre and decision, the view being described is that there isn’t a direction, or a centre, and that lots of technologies arrive that don’t yet have a purpose – cars being my example (but you could easily add the Xerox, the telephone, and the typewriter), so if they aren’t thought to be needed then why or how do they come to be?).
Paul Revere, Social Graph, Speculative Writing
The readings about networks and graphs. Facebook has what it calls a social graph, which is the data it maps about all our connections. I can’t do the mathematics behind it, but it is potentially very powerful, as this post from Ditte shows. In a similar vein when the Snowden story broke recently there were arguments that if the government harvested all this information about you, and you weren’t doing anything wrong, then what was the issue. (We’ll put to one side questions about sovereignty, privacy, the assumption of privacy and so on.) Sociologist Kieran Healy, using a social graph, wrote an extraordinary (speculative – note it is framed as if written from London in 1772, calls its data set Bigge Data – as in ‘olde worlde’ – and mentions an upcoming EDWARDx – TedX – talk) blog post that used this same mathematics and theory to ‘prove’ that Paul Revere was a terrorist. For those that don’t know, Paul Revere was the person who rode through Boston (there is literally a line painted on the road, in Boston today, so you can retrace his famous ride) yelling that the “British are coming!” and alerting the American patriots to the oncoming British soldiers in the American Revolution. He essentially set up an intelligence unit. He is the American hero (patriot, solider, prosperous silversmith, Bostonian, subject of a famous poem), and as Healy shows, by using the social graph (nodes and links) you can demonstrate that Revere was a hub, and therefore a terrorist. As Healy writes:
What a nice picture! The analytical engine has arranged everyone neatly, picking out clusters of individuals and also showing both peripheral individuals and—more intriguingly—people who seem to bridge various groups in ways that might perhaps be relevant to national security. Look at that person right in the middle there. Zoom in if you wish. He seems to bridge several groups in an unusual (though perhaps not unique) way. His name is Paul Revere.
Once again, I remind you that I know nothing of Mr Revere, or his conversations, or his habits or beliefs, his writings (if he has any) or his personal life. All I know is this bit of metadata, based on membership in some organizations.
The point he is making is that just based on social links a lot of information is known, but then add one or two assumptions (as he points out, he knows nothing about these people) and it is easy for this information to shift from being information, to knowledge, to an exercise of unreasonable power.
Voxies
Daniel J on notes from the first part of last week’s unsymposium. Ditte has stuff on data mining and how a shop could know if a customer was pregnant, and Tamrin went seeking out more information about small world networks, and was successful.
Big Lev
Dominic on Manovich on stories and databases and long tails and YouTube. Courtney on database, narrative, games. Boglarka and databases and narrative. Samuel picks up the semiotics of Manovich with the paradigm versus syntagm discussion. Isabella has a good gloss on Mr Lev Manovich’s essay. Brittany links to a biography. Tamrin discusses narrative and database. Tom on games, database, narrative – friend or foe? Courtney has a YouTube clip explaining what a database is and why they’re useful. And Courtney on the reading and how for Manovich the world is just a big collection of stuff (a database). Begs the question, is narrative then a less ‘authentic’ depiction of the world than a list? And Rebecca on games, narrative, databases, lists and stories.
This Week Was Bought to You By…
Shannen digs up some supplementary reading on technique and technology (well done). Anna C with notes. Victoria L, with streamed notes that seems to have kept up well. Brittany has dot points, and Patrick writes about codes, making, and rectangles. Tiana received chocolates, and thinks about nature, technology, culture. Tess on Bacon numbers.
Specular (Not Speculative)
Lauren on the ‘specular economy’ which is not only about how we think we want to present ourselves but also how extensive networks now are. If as we saw with Kevin Bacon it is easy to get from one person to another then imagine how trivial it is for someone you say something unpleasant about to actually hear about it.
Small World Networks, Scale Free, Kevin Bacon
My riff in response to Brian’s comment that the 80/20 stuff isn’t what really matters in the reading.
- the internet is scale free – you can add and add to it and it doesn’t fill up (unlike a room, a book, film, and most other of our media)
- it is made up of nodes (in social networks outside the internet these are people, in social networks inside the internet like Facebook these are generally people), which are small ‘things’ that can have connections to other similar things (friends, acquaintances, links from one web page to another)
- preferential attachment means that some nodes are more likely to want to be connected to other nodes (in my academic hypertext essay one node got more links in and out because it turned out to the heart of the argument I was making, because it is was an essay this was why this one node was preferred, in a blog you might link to a blog that is authoritative (you value) in the field that you also write about, you might just link to a friend’s blog)
- as a result of these three things hubs form, which have lots of connections in, and often out
- interestingly hubs have very weak connections – you don’t know them (a strong connection)
- and so a small world network arises
So it isn’t random, it isn’t disordered, it isn’t chaotic. A structure emerges that is understandable. But it emerges, the shape isn’t known in advance. This too, in many ways, is the opposite of what we think the world is.
A small world network means that because there are links, and hubs, it is quite simple to get from one point in the network to any other. Because there are densely connected hubs links follow a power law. A power law tells us that a few have a lot, but also that most of the material is in the tail, which is why niches now really matter.
Blogs, Opinion, Knowledge
Opinions, argument, the university and the coffee house. Read some interesting things in the blogs about the blogs and the encouragement of opinion and reflection. These are good conversations to have, and while these sorts of questions get discussed earlier in the semester they really don’t make much sense until we’re in the thick of it. (We really only learn by doing, to think otherwise is to think you can teach someone how to ride a bike by talking about it, so too with blogging, you need to do it to begin to understand what the issues are.) Anyway, the blogs. Let’s be blunt. Everyone has an opinion, and with blogs everyone has an opinion that can be broadcast. We don’t use blogs for this. As a university with you in a degree program while you can certainly happily express opinions, what we are wanting to develop, model, and endorse, is what I’ll call scholarly opinion. This doesn’t mean essays or objective third person writing (bugger that). What it does mean is to discuss things driven and informed by ideas, with evidence. This is what you do when you write or talk about things you know about. If you know about cycling you don’t just say Eddy Merckx is a better rider than Peter Sagan, but you make an argument for why. We all do this for the things we know and care about. As knowledge makers and users we need to do this too with ideas, so the key role of the blog – from the point of view of the subject – is to think about things. This means ideas, with evidence, that make propositions. This is different to opinion (I think Essendon sucks versus ‘there’s a cultural problem at Essendon because). One is (dumb) opinion, one is research, argued, and evidenced. We’re not journalists, but we are knowledge creators, and knowledge is not opinion.
All the Faces on Facebook
Have a look. This is what happens when we make networks of bits and loose connections. Services are porous to each other, so someone could make a service that pulls this data from over there, and does this with it.