Digg and the ‘Non-Editorial’ Fragmentation Machine

July 2nd, 2008

Bernhard Rieder points to an interesting interview about a not so surprising recommendation technology rolled out by Digg. The recommendations engine compares a user’s ‘digging’ of stories to the digging of others, while stories are being categorized in a variety of categories. It recommends stories that are digged by the users that are digging most similarly, in the categories you digg in. (I think this must be it) The part in the interview about the “editorial” is indeed intersting.  Kast states that Digg users do not want anything “editorial”. They want to choose by themselves.

I wonder if that is correctly interpreted (I think they don’t like this kind of stuff), but it is remarkable anyway.

Why people would people not like editorial? If I compare my first experience in an American diner (being asked twenty questions wwhen ordering a simple hamburger) to one of the best meals I ever had in a restaurantt in Rome - (no menu, one price,  no choice ) i know the model that I like. There is a certain sense of overestimation of oneself involved in not liking editorial and at the same time you underestimate your ability and knowledge to find the best, and not just something.

But, the problem is that editorial is used in the sense of ‘ open’, ‘no human involvement’ and ‘automated’. I have become increasingly convinced that the control over the selection process of these systems is still editorial. It might be distributed (over users) oepn (no preventive check) and automated (by algorithms) and the responsibility of the platform provider might be different from publishers for a number of reasons, but the service is editorial none the less. Digg has simply created an automated voting system for what goes into the newspaper. That is one model. The expert journalist gatekeeper model is another and there are many others and models in between. I still have to study more how far newspapers online are automated in their personalization, but the readers web experience is surely trying to be optimized as well.

Finally, the recommendation of stories that you could have digged yourself might be inefficient, like the recommendation of possible friends on Facebook that are already your friends. You dont need Facebook for that, do you? It is an excellent example of the Daily Me aspect of some online services, the idea that we are creating echo chambers, information cocoons, and that our society will be doomed because of fragmentation (joking). I do not believe this argument, but I do believe that some of the distributed automated editorial control is very mediocre.

2 Responses to “Digg and the ‘Non-Editorial’ Fragmentation Machine”

  1. Bernhard Rieder Says:

    Hi Joris,

    I wholeheartedly agree with your assertion that even automated models are editorial in a sense. The problem is that *how* they are editorial is still pretty unclear - our understanding of algorithmic models for agenda-setting is still limited due to the volume of data but also by the general lack of transparency when it comes to commercial sites. Having a rough understanding is often not enough. I remember working on a clustering algorithm once and even the slightest change in parameters would strongly affect the outcome…

    best,
    B.

  2. Bookmarks about Fragmentation Says:

    [...] - bookmarked by 3 members originally found by h4ppy on 2008-12-03 Digg and the ‘Non-Editorial’ Fragmentation Machine http://www.jorisvanhoboken.nl/?p=169 - bookmarked by 1 members originally found by losthearts101 [...]

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