Non-Linear Communication (a.k.a. Being Neil Postman’s Bitch)

In Academia, Marketing, Philosophy, Technology by J Michel Metz3 Comments

Everyone has some brush with fame. In my life I’ve been fortunate (or cursed, depending on how you look at it) to have several moments where I have been exposed to either great, popular, or paradigm-shifting people. When I was a freshly-minted Ph.D in the 1990s, I was a rising star in the field of Media Ecology and found myself attracting the attention of none-other than Neil Postman, who was most amused to call me “the poster child of new technology.”

One year I was on a panel with Neil discussing  “The Greatest Communication Idea of the 20th Century.” I needed something that was obvious, but so rudimentary that it needed to have a huge impact. While McLuhan’s “medium is the message/massage” was an obvious one, as was Harold Adams InnisEmpire and Communications, I had a gut feeling that there was something that was even more fundamental.

In my heart I knew that packet switching – the basis for the way the Internet sends messages – was critical to our overall metaphor of the way communication works. I knew that multipathing was as much of a human condition as a technological one, and understood that the technological models of information transfer derived from human communication patterns rather than the other way around (this is what caused Neil to make the “poster-child” crack). Neil may have been teasing me (he didn’t do “gentle” teasing), but at least he didn’t dismiss me.

Non-Linear Communication

Still, I knew it in my gut that this was critical. I knew that by breaking up the paradigm of communication-as-linear was crucial: this thought process was leading us to many misunderstandings of how we humans actually exchange meaningful information, as well as how that in turn affects our culture-building exercises.

Thinking about communication as a linear process could not explain why I was so excited about the revelation I made as a Masters student – that the model of computer-mediated communication was the software. That is, the mechanisms behind what formed social communities online was the capabilities and limitations of the software that people used. For instance, you cannot treat a social media strategy with Facebook, MySpace and Twitter the same not just because of the audience, but because the characteristics of the medium is different across each forum.

Communication-as-linear left us with only a “so what” question, and nowhere to go. The reason why packet switching was such an important coup for communication theory was that it took communication out of the realm of linear dynamics and into discrete, non-linear movement.

Too Much Noise

Too much noise.

Communication theory has been constantly troubled with the issue of “noise,” and the attempt to reduce it – or even eliminate it – from the communication loop process. Pick a model – and “noise” will be seen as the element to be minimized or, worse, seen as the afterthought to the core of source-receiver-feedback purpose of communication through any medium of choice.

The means of communication that involves packet switching provides us with a huge number of metaphors. We can see the breakout of communication into packets on every fractal level – letters, words, sentences: physical length requirements. Or we can look at them in terms of discrete memes, semantics, or other bundles of meaning.

Packet-based comprehension of communication gives us incredible explanatory power. It helps us understand the ebb-and-flow of dialog patterns (e.g., why we seem to run into natural pauses during group conversations every 7.5 minutes). It helps us understand the autopoeisis of email threads (or even comment threads on blogs). It helps understand how to correctly identify inefficiencies in communication – both in syntactic and symantic terms – in any medium.

Nonlinear communication explains much of behavior that is unexplainable – at least, elegantly – by linear metaphors. The jumps in syntax and semantics, timing, the rapid adaptability to software nuances, which in turn creates entirely different “feels” of culture within various media – all of these can be explained more conveniently and parsimoniously through a good understanding of the nonlinear dynamics.

This was the piece that was missing, the connection that I had failed to make when Neil decided to poke fun at me. I had been looking at linearity as the norm and not the exception. If you look at communication as linear then the revelation about the software model would mean that we have to make brand new linear connections for each different communication software metaphor.

But we don’t.

Packet Switching

Only by using a discrete, non-linear form of communication – a packet-based metaphor – can we adequately explain the ease of switching from one program to another, from one form to another…

…from one group to another.

This, too, was the missing piece from my dissertation: the process of affiliation is a process, yes (I was correct about that), but a non-linear process (and thus the source of my fundamental error about the cause-and-effect of how people become affiliated with groups).

When I was looking at how groups were formed, and the social psychology of groups, I had learned the wrong lessons from history. I had maintained the road of affiliation-as-a-linear process, albeit one that changed directions when feedback was introduced.

What I should have realized was that packet-based affiliation would be a clearer explanation. We intuitively see the people we’re affiliated to as our own imaginary fractals, and through the swirling self-emergence of these patterns in our minds and hearts do we come to recognize the same patterns as others. This is not something that can be maintained, however, via linear (e.g., circuit-based) communication patterns.

Strange Attractor

This also explains how we can have the same people in different communities providing us with different perceptions about our affiliation fractal. The software programs that allow us to behave in this non-linear fashion provide us the strange attractor – the natural boundaries into which our communication patterns will fall. That strange attractor becomes our own internal, imaginary pattern that defines our groups and how we affiliate within it.

So what?

By understanding this approach we can see that human communication patterns are a bit more understandable, especially when you start examining the role of social media. This is a merging of both the audience and the medium  – which can be important for determining how to approach understanding the appropriate social media strategy, regardless of whether you represent yourself or a company.

Having a social media strategy is a lot like trying to nail Jell-o to a wall. While it can be done, it’s not easy and needs to be accomplished with care. Having a better understanding of the way people communicate – and by extension how they affiliate with one another through the Internet – can strengthen the approach significantly.


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  1. Hi,
    Brilliant ideas!
    Nonlinear communication — packet switching – packets on every fractal level – strange attractors – I get the sense these are brilliant ideas. Do you see these ‘packets’ as bundles of meaning found within a fractal web of human perception? Are there common patterns that identify them as bundles of meaning? Have you expanded clarified these ideas for a general audience?

    1. Author

      Hi Bill,

      Thanks for the great comment (and encouragement). I began breaking things down a bit for a general audience but got pushed to the back burner a little as some more pressing obligations took hold. I’m still planning on working on it, though, and now that I can see that it’s generated some interest it certainly gives me some motivation.

  2. Hi Michel,

    I would like to encourage you to perhaps clarify a couple of ideas that in turn might motivate you to take a closer look this topic. It seems to me there are common nonlinear ‘packets’ bundles of meaning that have their own unique (fractal-based) performance characteristics. As I understand nature’s fractals they tend to be faster more frugal and effective than many manmade constructs.

    How might we apply these ideas to collaboration as a way to improve the process; to significantly improve effectiveness and to make it easier for more people to become better collaborators?

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