Quite a few of you have posted this:
Month: September 2013
Flux
Thanks to Samuel for this bit of software. Flux, adjusts screen temperature (colour temperature), so not just ambient brightness but it’s colour values. It’s a good idea. Caveat. I haven’t used it. Just sayin’.
More Unsymposium Thick Description
No idea where Nadine pulled these from, they read like some odd episode out of West Wing, but a weird list of coincidental things in history, some of which make you go, “really?”. It isn’t that one caused the other, but in thinking of history as linear the simultaneity of the world gets completely lost. History didn’t happen then, it must be with us now in some way (history is what is remembered now of then). Intertwingled. All the way down. David thinks about hypertextual reading for things that aren’t hypertext (we do this with most of our media these days) and the importance of the link. A link is treated by Google as a sort of endorsement, that a link from that term or phrase, to that page, means there’s probably some relation between the link text and the destination, and this is a very important part of how Google ‘understands’ the web as a reputation network – links to a page build its reputation. Brittany has a brief but useful list of points to ponder.
Tiana wondered about games and narrative. Let’s be clear. There are three things that matter to this question. Play, games, and stories. Every known culture has had each, but they are not the same as each other. I can play without needing to win. I can play with stories, I can play with words, I can play games. Games are things that, like play, have agreed upon (if temporary) rules, but games are ends directed, games are things you win. Remember play does not have to include winning, games do. Stories we read and try to understand. They can be playful (in English we use the same word for play as in children playing, and playing a game, other languages use different words for this), and we can play with language or film in telling these stories. But when we ‘use’ a story we don’t play it like a game, there is nothing to win. (And I can play many video games that have stories and win them, paying little if any attention to the story.) Games don’t need stories to be games. They can use stories, sure, but they don’t need stories. Games, not video games, but games as a general category. As I used as an example, Tetris. The argument isn’t about whether games can use stories (that’s a trivial argument), it’s whether narrative is fundamental to games. My view is that if you can have games that don’t have any ounce of narrative in them (which is different to what we might narrate about them afterwards) then narrative is not a fundamental requirement of a game. They’re different sorts of things. They can be mixed, but so can oil and water.
Networky Networks
Cuong on the long tail, and particularly notices Anderson’s comments about scarcity. This is something that the first and second lectures picked up on, where I pointed out that I came to university because of scarcity (library, films, experts, technologies) but that this scarcity is gone, so why come now? Same argument Anderson makes about going to the video store. Tony discusses the long tail, and is surprised at the mention of Kazaa, this just shows how quickly things change here, where we often measure an internet year as a dog year, so 1 year online = 7 years in the real world. Why? This reflects the pace of change and development online. Anita discusses the 80/20 rule and scale free networks, wondering if they are natural. They are, which is part of what these people demonstrate, our bodies, for example, turn out to be scale free networks with a power law distribution in terms of the number of proteins (which are out basic blocks) and how many of these different proteins are involved in how many reactions. A small number (crazy small) are involved in a heap. Nature, including us.
John and Andrew
Tess on some ideas that come up for her from the Potts and Murphie reading. Technology, society, culture, chicken or the egg? Arthur (who neatly notes that the author’s name’s could well be RMIT’s ‘private’ cafe) discusses the reading in relation to defining concepts of technology. That technology is not a tool, but a system is important (and so it is good to think about what a system is, and what that means). On the other hand we have culture, which today, is very hard to conceive of outside of a relation to technology (indeed someone like Jacques Ellul argues that culture is now a part of technology, not the other way round) – a proposition that first struck me as odd, and counter intuitive, until I thought about it and parked my cultural assumptions at the door. Georgina on the Watts reading does a similar move when she writes of technology that “[i]t’s oddly becoming a natural element of our world”. Yep, and it is odd to say that but really, how can we possibly think otherwise? What untechnologised moment have you had, anyone?
Hypertext Documentary
Denham is interested in interactive documentary. Won’t go into this much here but this is what Integrated Media One does, well, at least we make hypertextual online video works that are nonfiction.
O’Reilly as Example
Tim O’Reilly on his experience creating a major company in publishing (print and e) in the ‘internet economy’. It is a good read for many of you as it shows (I think) the connections between what we’ve been saying, how we’ve run the subject, and what O’Reilly has done, tried to do, and what matters. This is a business that is growing, and gives back in significant ways, so it is model to pay attention to.
More Voxies
Louisa has a bullet list of stations along the way. A semesters worth of material in 50 minutes. Patrick joins up NBN, infrastructure policy and network media. I’m with Patrick, the bigger, faster, more resilient it is built now, the better off we will be, it is the difference in defining useful as an extractive economy (dig it up, sell it) versus a knowledge economy. Olivia has another list of points from the unsymposium, very useful gloss. Millicent notices that she, like Brian, uses media ‘hypertextually’ (and so the debate that happens out in the real world is whether this is a good, or a bad, thing). Rebecca S thinks with her dad about Facebook, and dad points out that not very long ago MSN was all the rage (anyone remember MySpace?). My criticism of Facebook is that I think the network is the place for quality and niche, and I really really struggle to have that experience on Facebook. Let alone being inundated with dating ads (I’ve told them I’m married, and not looking, but they’re the ads I get??) One of my favourites is from Danielle with thoughts about games, stories, keyboards, recommendation engines and sharing the link love (link to others in the tail). This last point is incredibly important, it is what guarantees diversity and depth to the web – for all the reasons the last two week’s of readings have described. Closely followed by Lauren M who realised (very well done) that when I described hypertext as a post cinematic literacy, and that meaning is created outside of the shots, that what I was simply describing was the Kuleshov effect. Yep. Hypertext figured this out quickly, most other interactive media hasn’t. Rebecca M has another node come load of dump notes from the unsymposium… More to come…
Recommendation Engines
Was off my game (not sure you’d notice) Tuesday afternoon so wasn’t very clear. In relation to recommendation systems and things like FaceBook and Amazon, specificity here matters. They both have ways of recommending things but they are quite different in how they work, and why. FaceBook is about selling ads to advertisers, just like TV and newspapers. So when it puts ads in there it is using what it thinks it knows about you, based on what you and your friends have done on FaceBook in the past, combined with how much advertisers are willing to pay for their ad to someone that Facebook has defined as like you. So this is not a recommendation system, it is an advertising regime and the algorithmic systems that Facebook uses are about targeting advertisers to you. This makes it fundamentally different to the recommendation algorithms used by services such as Amazon and iTunes because for these latter services there is an enormous catalogue of material and as retailers they don’t care which one you buy, just that you buy. Facebook, on the other hand, since it sells ads which, as ads, want you to buy that thing rather than some other thing, has to care about what you choose and why – this is the entire premise of advertising. (In other words the book shop doesn’t care which book you buy, as long as you buy a book they stock, though once in the book shop some publishers will use different point of sale advertising to try to get you to buy that particlar book. Amazon and iTunes music store are like the book shop, they just want you in the shop, Facebook is more like the publisher, they not only want you in the shop, but then they want to sell ads to those in the shop.) Advertising is not and cannot be driven by recommendation algorithms because, for Amazon and iTunes, these are anonymous peer driven (anonymous because you don’t know them, peer because funnily enough there are other people who seem to like things you do, and on that basis there’s a pretty good chance you’ll like what they like too.)
Amazon on the other hand uses its data, harvested from what people buy on amazon, to data mine it to build its recommendation system. This is not a lot more complicated than using what I buy to define my profile, and then matching it with similar profiles. Once this is done it is possible to make suggestions based on what other people who appear to be interested in the things I’m interested in are interested in (there’s a lot of interest there). However, it is not trying to sell me anything specific, it just wants to help me find new things, in particular things I might not have noticed, on the reasonable assumption that I’ve bought there before, so am likely to do so again. In other words things don’t appear because they’ve been paid to be there (which is Facebook), they’re there because lots of people who buy those books also buy these ones. Because of Amazon’s scale (how many sales it makes) it has an enormous amount of information from which it can build its recommendations. It also lets you rank and rate its recommendations, which is handy and of course lets their algorithm became better. iTunes recommendations work the same way, it is simply using sales information so that people who like Bonnie Prince Billy are also likely to enjoy Bill Callahan. What is of value here is that it usually only takes about two clicks to find stuff that you often don’t know, and you can then decide if you’d like to listen to it. So, in relation to producing recommendation hierarchies it is quite resilient.
Intent and Why?
Abby wonders about intention and meaning and the whole mess. She has a good question:
I walked away from this ‘unlecture’ thinking ‘well if you can guarantee intent, and authorship is such a flimsy notion, then why do we create?
In my own case the answer is because making in itself is pleasurable (we make music without audiences, dance without audiences, so creating often happens without the intention of an audience – all I mean is that creating is pleasurable. The next answer would be that I have things I want to say and share. I have to keep making and sharing precisely because their specific meaning never arrives. The things I make never quite say them right, and people don’t quite understand them as I thought they might, either. So we do it again.