This post is the fifth of a five part series on ‘using the web for documentaries‘, addressing the following points: the embeddedness of society in the internet, the political in the web, the politics of engines, the politics of tools, and the web as an anticipatory medium.

So tools have politics too. Society and internet are closely intertwined; massive amounts of data are put online each day, so Internet is often quite up-to-date. This brings us to the final part: the web as an anticipatory medium.
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Since 1998, and on paper since 1989 (Stemwijzer 2008), general elections in the Netherlands have spawned a variety of so called voting recommendation machines. These systems typically ask the user to answer some questions after which they offer the user a voting recommendation, based on the compatibility between his or her answers and the political parties. The questions are either based on the political party’s programs (Kieskompas 2008), or on its actual voting behavior in Parliament over the past few years (Politix 2008).

Since the birth of online social networking sites lots of people have, quite unconsciously, put their likes and dislikes on public display. They not only show with whom they affiliate, but also what kind of music, movies, food, or even brands they prefer.

We have developed a post-demographic recommendation tool derived from digital life software systems, while at the same time addressing them - based on the aggregated profiles of pals of political party leaders as they appear on the biggest Dutch online social network, Hyves. By providing appropriate visualizations we show both the demographics and the relations of a group of pals, and replicate the existing, arguably anti-participatory democratic, voting recommendation machines. Ultimately the goal is to raise awareness of one’s digital public self - one’s data body (Well.com 1995) - to create conscience of simple yet powerful profiling techniques, and the tools of the surveillance and control society. (Bogard 1996, Deleuze 1992). We intentionally chose to highlight the entertaining quality and lightness of peer-based behavior this society is so immersed in. In addition, this paper introduces and explains the term post-demographics (first coined by Richard Rogers in August 2007) in the context of control society.
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The first thing that gets your attention on eboman.info is the list of well known web 2.0 logos. Next to it, Eboman coupled the logos to his own interpretation of what the service is about. YouTube for example lists his low-res videos, Wikipedia contains his history (actually his story, but I’ll come back to that later), Kiko holds his performance agenda, etcetera. At the top left of his site there is a call for participation: “Upload your videos to YouTube and JumpCut and make audiovisual sampletracks with Eboman”.

It looks as if the guy understands what web 2.0 is all about. There are a million definitions of web 2.0, but some of the characteristics seem to be: the Network as a (service-) platform, user -generated and -distributed content, and network effects created by an architecture of participation (deep linking). Eboman clearly calls for participation, uses different web services for various content generated by him, and uses this domain as a starting point to them.
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Finnaly came around reading some articles i marked 2read long time ago.  Here an interesting quote from an article about yahoo buying del.icio.us and flickr

“In topology search, what you’re really doing is conferring to webmasters the privilege of deciding what’s important for everybody. They cast their votes on what’s important by building links - and they do it in a way that smears it out for everybody, so we all get the same results.” The concept of personal search and social search, he says, “democratises that process, and says ‘why should webmasters be the only authority we trust and confer that privilege to?’. Why can’t I pick other authorities of trust, like for instance my friends? What is their opinion?”

So instead of getting the same results as everybody who searches a term, you get results that are filtered through your social group. You choose your own peers - friends, family, colleagues, interesting strangers - and they provide your answers. And by including different levels of friendship, you can increase the size of your net dramatically. Even if you have just 10 contacts, and those contacts have another 10 each, that’s still more than 100 potential sources within two hops. The concept is useful, perhaps, but maybe not for everyone.

“If you’re trying to find the population of London, you don’t need social search,” admits Horowitz. “But if you’re trying to find a restaurant to eat at, a blog to read, or a plumber who’s reputable - the kind of things you depend on the expertise of others to know - that’s where the social search phenomenon comes in.”