The Knobs and Dials of Social Software

The Flow Past Web: even better than the RealTime thing

by Kevin Marks

(republished with permission from Epeus’ epigone)

The ‘RealTime Web’ may be a name we are stuck with, but it is still a misleading one. Real-time software is a well-defined field where computing has to complete or fail cleanly by a deadline, because latency is paramount. A two-way phone conversation is an example – if the delay between parties exceeds a few hundred milliseconds, normal conversation becomes impossible, and people have to formally take turns. This is because a true verbal conversation is a flow state, where you are both engaged and responding. With text, the latency requirement can be relaxed – historically conversations have been conducted by exchanges of letters with latencies in weeks. What’s happening is that all kinds of media are having their latency domains expanded.

Technological constraints used to make buffering audio or video prohibitively expensive, so they only domain they could work in was real time, hence Telephony’s interruptive call model, and Radio and Television’s ‘one way to many people at once’ model. As storage has got cheap and ubiquitous, these give way to answerphones, TiVo’s, iPods and YouTube.

At the same time, the latency of text has been moving the other way, from newspapers’ and mail’s daily cycles, to hours for webpages, minutes for blogs down to seconds for SMS, Twitter, Facebook and other activity streams. However, as audio and video have added persistence, text hasn’t lost it – we do have the ability to review and catch up with the past of our flows, or to re-point people to older points in time, as well as marking out times in the future.

Text’s natural parallelism means we are seeing new kinds of public flow states that we have become used to as private ones – hence the “Twitter is public IM” explanation; but the other addition needed to make this stable and not a cacophony is the semi-overlapping publics that mean we don’t all see the same flow, but that it is mediated by the people we choose to pay attention to.

Much of the supposed ‘Real-Time’ web is enabled by the relaxation of realtime constraints in favour of the ‘eventually consistent’ model of data propagation. Google Wave, for example, enables simultaneous editing by relaxing the ‘one person can edit at a time’ rule in favour of reconciling simultaneous edits smoothly.

As Robert Hof says: “Real-time” is actually a bit of a misnomer. Most of this activity doesn’t truly occur in real time, the way talking on the phone does, and social gestures such as sharing links with friends are just as important a part of the appeal as immediacy. Instead, we should think about a web that flows past, a web where the flow is important, as well as its past. The Flow Past web.

So, if one of the knobs of the social software for social flow dashboard is time, what other knobs and dials do we see? And how are different software solutions mixing these up?

How Twitter works in theory

It is said that an economist is someone who sees something that works in practice and wonders whether it works in theory. Twitter clearly works in practice – and if you want practical advice, watch Laura Fitton’s Tech talk at Google, or read her Twitter for Dummies. I’ve learned a lot from talking to her and others about this phenomenon, and I wanted to write about some theories that help me understand it.


At it heart Twitter is a flow – it doesn’t present an unread count of messages, just a list of recent ones, so you don’t have email’s inbox problem – the implicit pressure to turn bold things plain and get that unread number down. Instead, you can dip in and out of it, when you have time, and what you see is notes from people you care about.


Indeed, what you see are the faces of people you know with the notes they wrote next to them. This taps into deep mental structures that we all have to look for faces and associate the information we receive with people we decide to trust, through what we feel about them. This is also why automated tweets not by them are so obtrusive, as they break the trust. Using friends’ faces in ads is even more pernicious, as ads are by definition recommendations from people we don’t trust.


The key to Twitter is that it is phatic – full of social gestures that are like apes grooming each other. Both Google and Twitter have little boxes for you to type into, but on Google you’re looking for information, and expecting a machine response, whereas on Twitter you’re declaring an emotion and expecting a human response. This is what leads to unintentionally ironic newspaper columns bemoaning public banality, because they miss that while you don’t care what random strangers feel about their lunch, you do if its your friend on holiday in Pompeii. This is something it shares with Facebook and other social networks, but this brings me to another key difference, which is asymmetric connections.


Historically, web fora were open to anyone, leading to the tragedy of the comments, where annoying people showed up and spoiled things. Social network sites changed this by requiring mutual agreement on friendship, thereby making a natural in-group area where you only saw your friends’ comments. This also created a venue for the phatic behaviour, but it was rather self-limiting, as you ended up with piles of friend requests from vaguely unfamiliar people that it feels rude to ignore, creating another inbox problem.

This is analogous to the pre-web hypertext systems that insisted every link would be bidirectional, thereby preventing the power-law distributed link structure that builds a small-world network to connect the web and provides the basis for Pagerank. Being able to link to something without it having to give you permission by linking back is what enabled the web to grow.

Making following asymmetric is similarly freeing for social relationships – it means you can follow authors or film stars without drowning them in friend requests, and get the same phatic sense of connection with them that you get from friends.


The idea of Following means that the natural view we see on Twitter is different for each of us, and is of those we have chosen to hear from. In effect we each have our own view of the web, our own public that we see and we address.

The subtlety is that the publics are semi-overlapping – not everyone we can see will hear us, as they don’t necessarily follow us, and they may not dip into the stream in time to catch the evanescent ripples in the flow that our remark started. However, as our view is fo those we choose to follow, our emotional response is set by that, and we behave more civilly in return.

For those with Habermas’s assumption of a single common public sphere this makes no sense – surely everyone should see everything that anyone says as part of the discussion? In fact this has never made sense, and in the past elaborate systems have been set up to ensure that only a few can speak, and only one person can speak at a time, because a speech-like, real-time discourse has been the foundational assumption.

Too often this worldview has been built into the default assumptions of communications online; we see it now with privileged speakers decrying the use ofanonymity in the same tones as 19th century politicians defended hustings in rotten boroughs instead of secret ballots. Thus the tactics of shouting down debate in town halls show up as the baiting and trollery that make YouTube comments a byword for idiocy; when all hear the words of one, the conversation often decays.

Mutual media

The alternative model is one that is less familiar, yet is all around us – the spontaneous order that emerges from people communicating in parallel. We know this from market pricing, from scientific consensuses, and from human language, and are starting to see it harnessed in projects like Wikipedia that present a dynamic cultural consensus. What shows up in Twitter, in blogs and in the other ways we are connecting the loosely coupled web into flows is that by each reading whom we choose to and passing on some of it to others, we are each others media, we are the synapses in the global brain of the web of thought and conversation. Although we each only touch a local part of it, ideas can travel a long way.

Small world networks

This seems counter-intuitive too—we’re used to the idea of having an institution tell us what is news—but that is really a left-over anomaly from 20th Century mass media. In fact, social connections are a small-world network, that has the Six Degrees property that it is both locally connected, but can be traversed globally in a small number of jumps. Although online social networks are often not good models of real world ones, they share this feature, and Twitter amplifies it with both a low propagation delay and the enforced brevity that makes both writing and reading rapid.

As we are working to generalise the ideas seen in Twitter and similar sites through the Activity Streams work, I find it helps me to think about these underlying theories.


Okay, Kevin, so I hear the mixing board for social software might be seen as:

  • Flow or stock model?
    • (no memory→ store everything and count the store)
    • Ex – Twitter → Email
  • Personal
    • Faces → Author obscured
    • ex twitter/FB → wikipedia
  • Connections
    • asymentric → symmetric
    • ex twitter followers → FB friends with double opt-in
  • Publics
    • Custom view → All same
    • ex google/twitter → wikipedia
  • Scale up or scale out
    • small interconnected worlds → large uni-directional networks (show maps)
    • (hops through replication of boundary spanners or spreads through #of initial receivers reached)
  • Length
    • short form → long form
  • Mutual media?
  • Time
    • high/chaotic delay of asynchonous → asynchronous/approximal → synchronous