Category Archives: web 2.0

This preprint of a paper I have written about a year and a half ago, entitled Institutionalizing without Institutions? Web 2.0 and the Conundrum of Democracy, is the direct result of what I experienced as a major cultural destabilization. Born in Austria, living in France (and soon the Netherlands), and working in a field that has a strong connection with American culture and scholarship, I had the feeling that debates about the political potential of the Internet were strongly structured along national lines. I called this moral preprocessing.

This paper, which will appear in an anthology on Internet governance later this year, is my attempt to argue that it is not only technology which poses serious challenges, but rather the elusive and difficult concept of democracy. My impression was – and still is – that the latter term is too often used too easily and without enough attention paid to the fundamental contradictions and tensions that characterize this concept.

Instead of asking whether or not the Internet is a force of democratization, I wanted to show that this term, democratization, is complicated, puzzling, and full of conflict: a conundrum.

Published as: B. Rieder (2012). Institutionalizing without institutions? Web 2.0 and the conundrum of democracy. In F. Massit-Folléa, C. Méadel & L. Monnoyer-Smith (Eds.), Normative experience in internet politics (Collection Sciences sociales) (pp. 157-186). Paris: Transvalor-Presses des Mines.

German publisher Heise Verlag is an international curiosity. It publishes a small number of highly influential computer-related magazines that give a voice to a tech ethos that is at the same time extremely competent in the subject matter (I’ve been a steady subscriber to c’t magazin for over 15 years now, and I am still baffled sometimes just how good it is) and very much aware of the social and political implications of computing (their online magazine Telepolis testifies to that).

Data protection and privacy are long-standing concerns of the heise editors and true to a spirit of society-oriented design, they have introduced a concept as well as a technical implementation of a two-step “like” button. Such buttons, by Facebook or other companies, have of course become a major vector of user-tracking on the Web. By using an iframe, every button loads some code from Facebook’s server and sends the referring url (e.g. as an information. The iframe being hosted on the domain, cross-site privacy protections can be circumvented, the url information connected to an identifier cookie and, consequently, to a user account. Plugins like the Priv3 project block these mechanisms but a) users have to have a heightened level of awareness to even consider installing something like this and b) the plugin interferes with convenient functions like Google search preferences.

Heise’s suggestion, which they already implemented on their own sites, is simple: websites can download a small bit of code that implements a two-step procedure: the “like” button is greyed out after the page first loads and there is no tracking happening. A first click on the button loads the “real” Facebook code, and the second click provides the usual functionality. The solution is very simple to implement and really a very minor inconvenience. Independently from the debate whether “like” buttons and such add any real value to the Web, this example shows that “social” features like these can be designed in a way that does not necessarily lead to pervasive user tracking.

The echo to this initiative has been very strong (check the Slashdot discussion here), especially in Germany, where privacy (or rather Datenschutz, a concept less centered on the individual but rather on the role of data in society) is an intensely debated issue, due to obvious historical reasons. Facebook apparently threatened to blacklist at a point, but has since then backpedaled. After all, c’t magazin prints around 600.000 issues of every number and is extremely influential in the German (and Dutch!) computer landscape. I am very curious to see how this story unfolds, because let’s be clear: Facebook’s earning potential is closely tied to its capacity to capture, enrich, and analyze user data.

This initiative – and the Heise ethos in general – underscores that a “respectable” and sober engineering culture does not exclude an explicit normative stance on social and political issues. And is shows that this stance can be translated into technical models, implemented, and shared, both as an idea and as code.

When it comes to analyzing and visualizing data as a graph, we most often select only one unit to represent nodes. When working with social networks, nodes commonly represent user accounts. In a recent post, I used Twitter hashtags instead and established links by looking at which hashtags occurred in the same tweets. But it is very much possible to use different “ontological” units in the same graph. Consider this example from the IPRI project (a click gives you the full map, a 14MB png file):

Here, I decided to mix Twitter user accounts with hashtags. To keep things manageable, I took only the accounts we identified as journalists that posted at least 300 tweets between February 15 and April 15 from the 25K accounts we follow. For every one of those accounts, I queried our database for the 10 hashtags most often tweeted by the user. I then filtered the graph to show only hashtags used by at least two users. I was finally left with 512 user accounts (the turquoise nodes, size is number of tweets) and 535 hashtags (the red nodes, size is frequency of use). Link strength represents the frequency with which a user tweeted a hashtag. What we get, is still a thematic map (libya, the regional elections, and japan being the main topics), but this time, we also see, which users were most strongly attached to these topics.

Mapping heterogeneous units opens up many new ways to explore data. The next step I will try to work out is using mentions and retweets to identify not only the level of interest that certain accounts accord to certain topics (which you can see in the map above), but the level of echo that an account produces in relation to a certain topic. We’ll see how that goes.

In completely unrelated news, I read an interesting piece by Rocky Agrawal on why he blocked tech blogger Robert Scoble from his Google+ account. At the very end, he mentions a little experiment that founder Joshua Schachter did a couple of days ago: he asked his 14K followers on Twitter and 1.5K followers on Google+ to respond to a post, getting 30 answers the former and 42 from the latter. Sitting on still largely unexplored click data for millions of urls posted on Twitter, I can only confirm that Twitter impact may be overstated by an order of magnitude…

There are many different ways of making sense of large datasets. Using network visualization is one of them. But what is a network? Or rather, which aspects of a dataset do we want to explore as a network? Even social services like Twitter can be graphed in many different ways. Friend/follower connections are an obvious choice, but retweets and mentions can be used as well to establish links between accounts. Hashtag similarity (two users who share a tag are connected, the more they share, the closer) is yet another method. In fact, when we shift from interactions to co-occurrences, many different things become possible. Instead of mapping user accounts, we can, for example, map hashtags: two tags are connected if they appear in the same tweet and the number of co-occurrences defines link strength (or “edge weight”). The Mapping Online Publics project has more ideas on this question, including mapping over time.

In the context of the IPRI research project we have been following 25K Twitter accounts from the French twittersphere. Here is a map (size: occurrence count / color: degree / layout: gephi with OpenOrd) of the hashtag co-occurrences for the 10.000 hashtags used most often between February 15 2011 and April 15 2011 (clicking on the image gets you the full map, 5MB):

The main topics over this period were the regional elections (“cantonales”) and the Arab spring, particularly the events in Libya. The japan earthquake is also very prominent. But you’ll also find smaller events leaving their traces, e.g. star designer Galliano’s antisemitic remarks in a Paris restaurant. Large parts of the map show ongoing topics, cinema, sports, general geekery, and so forth. While not exhaustive, this map is currently helping us to understand which topics are actually “inside” our dataset. This is exploratory data analysis at work: rather than confirming a hypothesis, maps like this can help us get a general understanding of what we’re dealing with and then formulate more precise questions from there.

Since Yahoo recently ~sold its search business to Microsoft (see this NYT article for details) a lot of people where asking themselves what would happen to the Yahoo search APIs, which are in fact some of the most powerful free tools out there to built search mashups with. As Simon Wilson indicates in this blog post, some of them (Term Extraction and Contextual Web Search) are closing down at the end of August. Programmable Web lists 33 mashups that use the Term Extraction service and these sites will either have to close down or start looking for alternatives. This highlights a problem that can be a true roadblock for developing applications making heavy use of APIs. My own termcloud search and its spiced up cousin contextdigger use Yahoo BOSS and quite honestly, if MS kills that Service, these experiments (and many others) will be gone for good, because Yahoo BOSS is the only search API that provides a list of extracted keywords for each delivered Web result.

If service providers can close APIs at will, developers might hesitate when deciding whether to put in the necessary coding hours to built the latest mashup. But it is mashups that over the last years have really explored many of the directions left blank by “pure” applications. This creative force should be cherished and I wonder if there may be a need for something similar to creative commons for APIs – a legal construct that gives at least some basic rights to mashup developers…

Programmable web just pointed to a really interesting mashup competition. Sunlight labs announced the Apps for America contest and the idea is to attract programmers that will use a series of data APIs to “make Congress more accountable, interactive and transparent”. Among the criteria two stand out:

  1. Usefulness to constituents for watching over and communicating with their members of Congress
  2. Potential impact of ethical standards on Congress

The design goal is accountability and that indeed is a perfect case for society oriented design. While people in Europa love to scold the US for their lack of data protection and privacy laws, just looking at the APIs the contest proposes to use makes me salivate for something similar in France. If you look at the Capitol Words API for example, just imagine the kind of discourse analysis one could build on that. Representations of what is said in Congress that make the data digestable and bring at least some of the debate potentially closer to citizens. The whole thing is just a really great idea…

The concept of self-organization has recently made quite a comeback and I find myself making a habit of criticizing it. Quite generally I use this blog to sort things out in my head by writing about them and this is an itch that needs scratching. Fortunately, political scientist Steven Weber, in his really remarkable book The Success of Open Source, has already done all the work. On page 132 he writes:

Self-organization is used too often as a placeholder for an unspecified mechanism. The term becomes a euphemism for “I don’t really understand the mechanism that holds the system together.” That is the political equivalent of cosmological dark matter.

This seems really right on target: self-organization is really quite often just a means to negate organizing principles in the absence of an easily identifiable organizing institution. By speaking of self-organization we can skip closer examination and avoid the slow and difficult process of understanding complex phenomena. Webers second point is perhaps even more important in the current debate about Web 2.0:

Self-organization often evokes an optimistically tinged “state of nature” narrative, a story about the good way things would evolve if the “meddling” hands of corporations and lawyers and governments and bureaucracies would just stay away.

I would go even further and argue that especially the digerati philosophy pushed by Wired Magazine equates self-organization with freedom and democracy. Much of the current thinking about Web 2.0 seems to be quite strongly infused by this mindset. But I believe that there is a double fallacy:

  1. Much of what is happening on the Social Web is not self-organization in the sense that governance is the result of pure micro-negotiations between agents; technological platforms lay the ground for and shape social and cultural processes that are most certainly less evident than the organizational structures of the classic firm but nonetheless mechanisms that can be described and explained.
  2. Democracy as a form of governance is really quite dependent on strong organizational principles and the more participative a system becomes, the more complicated it gets. Organizational principles do not need to be institutional in the sense of the different bodies of government; they can be embedded in procedures, protocols or even tacit norms. A code repository like is quite a complicated system and much of the organizational labor in Open Source is delegated to this and other platforms – coordinating the work effort between that many people would be impossible without it.

My guess is that the concept of self-organization as “state of nature” narrative (nature = good) is much too often used to justify modes of organization that would imply a shift power from traditional institutions of governance to the technological elite (the readers and editors of Wired Magazine). Researchers should therefore be weary of the term and whenever it comes up take an even closer look at the actual mechanisms at work. Self-organization is an explanandum (something that needs to be explainend) and not an explanans (an explanation). This is why I find network science really very interesting. Growth mecanism like preferential attachment allow us to give an analytical content to the placeholder that is “self-organization” and examine, albeit on a very abstract level, the ways in which dynamic systems organize (and distribute power) without central control.

This is not a substantial post just a pointer to this interview with Digg lead scientist Anton Kast on Digg’s upcoming recommendation engine (which is really just collaborative filtering but as Kast says the engineering challenge is to make it work in real time – which is quite fascinating given the volume of users and content on the site). Around 2:50 Kast explains why Digg will list the “compatibility coefficient” (algorithmic proximity anyone?) with other users and give an indication why stories are recommended to you (because these users dug them): Digg users hate getting stuff imposed and just showing recommendations without a trail “looks editorial”. Wow, “editorial” is becoming a swearword. Who would have thought…

There are many things to be said about Clay Shirky’s recent book “Here Comes Everybody: The Power of Organizing without Organizations” and a lot has already been said. The book is part of an every growing pile of Web 2.0 literature that could be qualified as “popular science” – easily digestible titles, generally written by scholars or science journalists, which are generally declaring the advent of a new age where old concepts no longer apply and everything is profoundly transformed (knowledge, education, the economy, thinking, wisdom, organization, culture, journalism, etc.). The genre has been pioneered by people like Alvin Toffler and Jeremy Rifkin and it does now dominate much of the debate on the social, cultural and political “effects” of recent developments in ICT. There is of course merit to a larger debate on technology and the sensationalist baseline is perhaps needed to create the audience for such a debate. At the same time, I cannot help feeling a little bit unsettled by the scope the phenomenon has taken and the grip these books seem to have on academic discourse. Here are a couple of reasons why:

  1. There are actually very few thoughts and arguments in the whole “Web 2.0 literature” that have not already been phrased in Tim O’Reilly’s original essay. Granted, the piece was quite seminal but shouldn’t academia be able to come up with a stronger conceptual viewpoint?
  2. The books in question are really lightweight when it comes to anchoring their thoughts in previous scholarly effort. A lot of room is given to metaphorical coupling with the natural sciences (some keywords: swarms, ecologies, auto-organization, percolation, critical thresholds, chaos, etc.) but although most of these books talk about the future of work (prosumers performing collective wisdom, in short), there is very little interaction with the sociology of labor or economic theory. Sure, a deeper examination of these topics would be difficult, but without some grounding in established work, the whole purpose of scholarship as a collective endeavor is meaningless – which is especially ironic given the celebration of cooperation one can find in Web 2.0 literature
  3. As I’ve already written in another post, I find the idea that “participation” and “leveling of hierarchies” equates democracy deeply troubling. Richard Sennett’s argument that stable social organization and work relations are necessary prerequisites for true political discourse – politics that go beyond the flash mob activism often presented as prove for the new, more democratic age that is upon us – is ringing louder than ever.
  4. Much of the Web 2.0 literature is basically antithetical to the purpose of this blog. Shirky’s idea that the new social tools allow for “organizing without organizations” is largely ignoring the political power that is transferred to the 21st century tool maker and the companies that he or she works for. I’m not advocating paranoia here, but the fact that many of the tools that power mass sociability online are produced and controlled by firms that are accountable to their shareholders only (or the people that got them venture capital) is at least worth mentioning. But the problem really goes beyond that: the tools we currently have incite people to gather around common interests, creating and activating issue publics than can indeed take influence on political matters. But politics is much more than the totality of policy decisions. The rise of issue publics has coincided with the demise of popular parties and while this may look like a good thing to many people, parties have historically been the laboratories for the development of politics beyond policy. Europe’s social market economies are unthinkable without the various socialist parties that worked over decades to make societies more just. One does not have to be a left winger to recognize that the loss of the stable and accountable forum that is the political party would be at least ambiguous.
  5. While Web 2.0 literature is light on politics and serious political theory it is not stingy with morals. The identification of “good” and “bad” effects that 2.0 ICT will have on society often seems really at the core of many of the texts published over the last few years. But as point 4 might have shown, the idea of “good” and “bad” is really meaningless outside of a particular political (or religious) ontology. What actually happens is the understatement of a vague political consensus that takes a position antithetical to the premises of critical sociology, i.e. that conflict is constitutive to society.
  6. An essay stretched over 250 pages does not make a book. (I know, that’s a little mean – but also a little true, no?)

Don’t get me wrong, many of the books I’m referring to have actually been quite interesting to read. What worries me is the lack of more scholarly and conceptually demanding works but perhaps I’m just impatient. In a sense, “Digital Formations” by Robert Latham and Saskia Sassen already shows how sophisticated Internet Research could be if we switch off that prophet gene.

This is a very general question and there is no way to answer it in a rigorous way. But after reading many of the books and articles on “participatory culture” I cannot shake the feeling that the idea of non-organized organization will very soon be confronted with a series of limits and problems inherent to auto-organized social aggregation – inequality, intercultural strife, visibility of minority opinion, etc. – that will be difficult to ignore.

But there is a more practical reason why I ask myself this very question. Pierre Lévy actually used to work at my department and my laboratory has recently stuck up a cooperation with his research unit in Ottawa. We’ve been organizing a little seminar here in Paris where Lévy will be giving a talk later this month. When Lévy wrote “L’intelligence collective” in 1994, many people saw his proposals as sheer blue-eyed utopia and dismissed it rather quickly. The American reading of that text has since then become something like the bible of research on participatory culture, user-generated content movements, and so on. Interestingly, Lévy himself has been pretty silent on all of this, leaving the exegesis of his thoughts to Henry Jenkins and others. Why? Because Lévy probably never imagined collective intelligence as photo-sharing on Flikr or Harry Potter fanfiction. What he envisioned is in fact exemplified by his work over the last couple of years, which was centered on the development of IEML – Information Economy Meta Language:

IEML (Information Economy Meta Language) is an artificial language designed to be simultaneously: a) optimally manipulable by computers; and b) capable of expressing the semantic and pragmatic nuances of natural languages. The design of IEML responds to three interdependent problems: the semantic addressing of cyberspace data; the coordination of research in the humanities and social sciences; and the distributed governance of collective intelligence in the service of human development.

IEML is not another syntax proposal for a semantic web like RDF or OWL. It is a philosopher’s creation of a new language that allows mainly two things: facilitate the processing of data tagged with IEML sentences and help cross-language and intercultural reasoning. This page gives a short overview. Against the usual understanding of collective intelligence, IEML is really a top-down endeavor. Lévy came up with the basic syntax and vocabulary and the proposal explicitly states the need for experts in helping with formalization and translation. I must admit that I have been very skeptical of the whole thing, but after reading Clay Shirky’s “Here comes Everybody” (which I found interesting but also seriously lacking – I’ll get to that in another post though) there is a feeling creeping up on me that Lévy might yet again be five years ahead of everybody else. In my view, the mindset of large parts of research on participation has adopted the ontology and ethics of American-brand Protestantism which, among other things, identifies liberty and democracy with community rather than with the state and which imagines social process as a matter of developing collective morals and practices much more than the outcome of power struggles mediated by political institutions. This view idealizes the “common man” and shuns expert culture as “elitist”. Equality is phrased less in socio-economic terms, as “equal opportunity” (the continental tradition), but in mostly in cultural terms, as “equal recognition”. (Footnote: this is, in my view, why political struggle in the US has been, for many decades now, mostly about the recognition of minority groups while on the European continent – especially in catholic countries – “class struggle” still is a common political vector) In this mindset, meritocracy is therefore necessarily seen as ambiguous.

I believe that the most interesting projects in the whole “amateur” sector are the ones that organize around meritocratic principles and consequently built hierarchy; open source software is the best example but Wikipedia works in a similar fashion. The trick is to keep meritocracy from turning into hegemony. But I digress.

Lévy’s bet is that collective intelligence, if it wants to be more than pop culture, will need experts (and expert tools) for a series of semantic tasks ranging from cartography to translation. His vision is indeed much more ambitious than most of the things we have seen to this day. The idea is that with the proper (semantic) tools, we could tackle problems collectively that are currently very much out of reach; and this in a truly global fashion, without bringing everybody into the rather impoverished linguistic umbrella of globish. Also, in order to make search more pluralistic and less “all visibility to the mainstream” as it currently is, we will need to get closer to the semantic level. I don’t believe that IEML, in its current iteration at least, can really do all these things. But I believe that yet again, Lévy has the right intuition: if collective forms of “problem solving” are to go beyond what they currently do, they will have to find modes of organization that are more sophisticated than the platforms we currently have. These modes will also have to negociate a balance between “equal opportunity” and “equal representation” and make it’s peace with instituionalization.