Future of social web: system and practices

Jeremiah Owyang has posted his thoughts on what may come in the long-term for the social web, beginning with the increasing relevance of activities like friending: Why ‘Friending’ Will Be Obsolete. He writes that as the system learns about our behaviors, preferences, and relationships that it will be able to automate and supply information we normally have to declare explicitly today. I couldn’t agree more.

Jeremiah summarizes his model like this:

“The System: The system is the combination of all websites combined, it’s a massive data base of content, clicks, search terms, time on site, shared posts, wall posts, links, and tweets.

Teaching the System: Humans are constantly speaking in machine language, from use of hashtags in twitter, or boolean searches in Google, or even from the act of friending folks in your social network. All of these behaviors are humans teaching the system how to understand us, so it can better serve us.

The Intelligent Web: Software that is able to collect and make sense of all the data in the system and is able to deliver meaningful content back to people in context — often without us saying or gesturing that we need it.”

The web was built on links between documents — objects — and since it’s inception has grown to accommodate not only many different object or media types, but their relevance, popularity, and other measures of use also. In fact links on the social web need not always point to the same thing. Social navigation in the form of a top-ten, for example, points to not only a changing set of top ten items, but updates itself as it is used, thus reflecting social use.

Behind Jeremiah’s vision of the future is the system’s interest in capturing and recontextualizing its own use. If the static web was merely a network of static connections, the social web is a dynamic network of changing connections. If we assume that social use will remain a priority for web builders and designers, applications and their businesses, then the relevance of information provided by the web will likely be qualified along two axes: the personal and the social, or the particular and the general. The next generation web, in systems speak, is a second-order observer system. Meta data supplies a second order observation of its own use: the web knows not only what it publishes but also how users interact with it.

Because the system is open, is dynamic, and is always in use, the new system is not a static collection but a dynamic and changing set of connections — connections whose relevance to an individual user and to the audience in general change over time. The next generation system has time. The first generation system did not.

I see, or would like to imagine, a system whose links are no longer document links but are instead “views.” Each view (link) of information might then take into account meta data along our two axes: one user-centric, the other social-centric. A user centric view would be informed by my past history and tacit (learned) and explicit (declared) preferences. My tastes and interests, in other words. The social-centric view would be informed by social usage, social ratings and votes, interests, trends, and so on. I might use sliders to set the view I want on a social site — stuff for me or stuff socially organized.

There is another development coming for the next generation system, and that is the temporal organization of system (vs spatial organization). The topic comes up in discussions on lifesreaming and flow apps (which I’ll discuss soon), and often takes the form of talk-based apps vs page-based apps. Twitter, for example, is not page based: it lacks navigation, topical organization, topical layout, and so on, choosing instead the temporal organization of content used by time-based apps like IM, chat, and email. As more of these apps innovate, become more visual, and go mobile, time-based interaction tools will mature. We’ll have two modes of interacting with the system: from within the river of flow or from its shores: watching as it streams past.

Innovation of late may have produced many look-alikes. But it’s when things begin to look alike that exploration begins anew at the margins.

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