Monthly Archives: November 2010
I just saw that the good people from sociomatic have prepared a nice little slideshow on how to use gephi to analyze social network data extracted from Facebook (using netvizz). This is a great way to start playing around with network analysis and the slides should really help with the first couple of steps…
The use of computers in the humanities has a long and fine history. What is striking though is how lucid scholars reflected on their tools even in the earliest days. Here’s a beautiful citation by Irwin C. Lieb from a text published in the the inaugural issue of Computers in the Humanities, a journal started in 1966.
The great advances which have so far been made with computers have been in those fields where we find countable items or have ready substitutes for them. The real or seeming extraneousness of computer studies for the humanities is owed to the fact that, in the humanities, what are most important are, if items at all, items that we can’t count, or can count only most artificially. We know, for example, how little definite we mean in saying that we have two or three ideas, that there are four themes in a play, or that there were this or that number of historical events. Our “counting” is not the counting of items that were somehow there separate, waiting to be pointed out; it is a “counting” in which judgments themselves mark out what come to be the items that we count. Apart from the judgments, there are no separate items. Therefore, no technique of counting such items so as to yield, for the first time, a judgment or a summary is possible at all. But, granting that this sort of limitation is inescapable, computers could, it seems, still come to have a more vital use in the humanities than we have seen so far.
[…]
The suggestion, then, is that some of the simplest but most important work to be done in deepening the usefulness of computers for the humanities will be in imagining those schemas by which we will model what we know cannot be modeled undistortedly: — ideas, themes, events and even more importantly, insights, appraisals, and appreciations. There are, there must be, revealing models for all of these. And as we think of them, and then use them in the humanities, the achievement for us will come as we feel out just what the distortions are, as we make the right mistakes. For as we see them as mistakes, we will penetrate further and still more appreciate what we are most concerned to understand. With the possibilities for computer studies of depth and importance in the humanities seeming still so genuine, it would be a mistake, I think, to curtail our exploration of them soon.
When it comes to scrutinizing companies for their actions and policies concerning control over information, privacy issues, and market dominance in areas related to public debate, large media conglomerates have been the traditional objects of analysis. More recently, Internet giants such as Google and Facebook have been critically examined and when the hype levels off, Twitter will probably be the next on the list. Malcolm Gladwell’s recent piece in The New Yorker may very well be an indicator of things to come.
Whether the issues related to “social media” are important or not, I have the feeling that the debate overshadows questions and problem fields that may in fact be much more important. The most obvious case, in my view, is the debate on privacy on Facebook. While the matter is not irrelevant, I think that e.g. present and future state-run information systems such as the french EDVIGE, a central police database that assembles all kinds of personal information concerning select persons “of interest”, have been overshadowed by debate on whether your employer can see the pictures that document your drinking binges after somebody (you?) put them on the ‘Book. There is a certain disequilibrium in how Internet researchers and critics distribute their attention that has allowed all kinds of things to pass below the radar. But there is one event that has really shook me up recently, both because of its importance and the lack of outcry it garnered, at least in my echo chamber: the acquisition of the Reuters group by the Thomson corporation in 2008 and the creation of Thomson Reuters, an information giant second to none.
Thomson Reuters market divisions
I have stumbled upon Thomson Reuters a couple of times over the last years: first, when I researched the history of citation indexing, I learned that Thomson Scientific had bought the Institute of Scientific Information (and their Web of Science citation index megabase from which things like the notorious Impact Factor are calculated) in 1992; then again when I noticed that the ClearForest API for term extraction had be renamed, remodeled, and rebranded as OpenCalais after Reuters bought the company in 2007; finally, last year, when I noticed that the Reuters video platform appeared more and more often in articles and links. When I finally started to look a little closer (NYSE:TRI) I was astounded to find a company with a market cap of $31B, annual revenues of $13B, and 55K+ employees all over the world. Yes, this is no Apple big, but still very, very big for a company that sells information.
I knew Reuters from my studies in communication science as the world’s biggest news agency (with roughly one and a half competitors: Associated Press and Agence France Presse) but I had never consciously registered the Thomson company – a Canadian Family business that went from the media (owning the London Times at one point) to publishing before transforming itself in a rather risky move into a digital information broker for all kinds of special fields (legal, health, finance, etc.). Reuters was a perfect match and I really wonder how that merger went through without too much hassle from the different regulatory bodies. Even more so when I found out that Reuters actually had devised a very spicy regulatory clause when it made its IPO in 1984: to avoid control over such a central source of information, no single shareholder would be allowed to hold more than 15% of the companies stocks. Apparently, that clause was enacted at least once when Murdoch’s News Corporation (already holding 15%) bought a competitor that also owned a piece of Reuters and consequently had to shed stock to stay below the threshold. The merger effectively brought the new Reuters Thomson under full control (53%) of The Woodbridge Company, a private holding that represents the Thomson family.
Such control over a news agency (and the many more specialized services that are part of the giant’s portfolio) should give us pause in the best of times when media companies are swimming in resources, are able to pay good money for good journalism, and keep their own network of correspondents. But recent years have seen nothing but cost cutting in journalism, which has led to an even greater reliance on news agencies. I wager that Google News would work a lot less well if people actually started to write their own copy instead of remodeling Reuters’ and AP send outs.
But despite these rather traditional – but nonetheless crucial – concerns over media ownership and control, there is a second point that is somewhat closer to my area of expertise. I have recently been thinking a lot about how to best phrase criticism of the assumption that digital networks necessarily lead to decentralization. Thomson Reuters – but also other information giants such as Google and Facebook – is a great example for how digital technologies can lead to quite impressive cost reductions for economies of scale and, consequently, market concentration. These arguments should be taken into account:
- While the barriers of entry to the Internet are really low (you can have your own blog in minutes), scaling up to millions of visitors is a real challenge. Building your own datacenter is a real bump in the learning curve and to get over it, you need to make certain investments. But once you pass that bump, scaling suddenly becomes cheaper again because you have the knowledge ressources and experience that can now be applied to make the datacenter grow. One of Google’s strengths lies in this area and this immensely facilitates branching out into new information ventures. The same goes for Thomson Reuters: they master platform technology and distribution technologies for all kinds of contents and they can build on that mastery to add new things to serve information to a globalized planet. To use the language of the long tail: there may be more special interest information that can find an audience with shelve space becoming effectively unlimited; but there is also no longer a need for more than one shelve.
- The same goes for a more elusive matter: the mastery of information. The database techniques and indexing tools we use to store information – as well as the search and data-mining algorithms – can be very easily transported from one domain to the next. While it may be (very) difficult to create useful search tools for medical information, once you have built them it is rather easy to adapt these tools to, let’s say the legal domain. Again, this is what makes Google strong: basic search technology can be applied to advertising, books, mail, product prices, and even video if you can do automatic transcription. With the acquisition of ClearForest, Thomson Reuters has class-leading in-house data-mining and this is not something you can get by simply posting a couple of job ads in the local newspaper. Data-mining is extremely useful in areas where fast decision-making is crucial but also when it comes to building powerful search tools. Again, these techniques can be applied to any number of fields and once you have the basics right you can just add new domains with very little cost.
These two points go a far way in explaining why the Internet has seen the lightning fast emergence of network giants over the last couple of years. I really don’t want to postulate yet another “law” of the Net but I believe that there is something to this idea of the bump: it’s easy to have a basic presence on the Web but it’s hard to scale up to a large audience and to use advanced computational techniques; but one you pass the bump, the economies of scale kick in and from there it seems like there are no barriers to growth. The Thomsons have certainly made that bet when they acquired Reuters and so far, it seems to work out quite nicely for them.
I hope we can find a means to extend critique from questions of ownership into the heart of the (informational) beast and come up with better ways to understand how the still ongoing shift to exclusively digital information affords new means of handling and exploiting that information – with organizational, economic, and political consequences. While that work is starting to take shape for consumer companies like Google that are in the spotlight, there is surprisingly little on invisible network giants like Thomson Reuters that cater mostly to professional clients.