“The Shannon and Weaver Model”

First things first: some housekeeping.  Last week I launched a Facebook page for The Late Age of Print.   Because so many of my readers are presumably Facebook users, I thought it might be nice to create a “one-stop shop” for updates about new blog content, tweets, and anything else related to my work on the relationship between print media and algorithmic culture.  Please check out the page and, if you’re so inclined, give it a like.

Okay…on to matters at hand.

This week I thought it might be fun to open with a little blast from the past.  Below is a picture of the first page of my notebook from my first collegiate communication course.  I was an eighteen year-old beginning my second semester at the University of New Hampshire, and I had the good fortune of enrolling in Professor W—-‘s introductory “Communication and the Social Order” course, CMN 402.  It wouldn’t be an overstatement to call the experience life changing, since the class essentially started me on my career path.

What interests me (beyond the hilariously grumpy-looking doodle in the margin) is a diagram appearing toward the bottom of the page.  It’s an adaptation of what I would later be told was the “Shannon and Weaver” model of communication, named for the electrical engineer Claude Shannon and the mathematician Warren Weaver.

CMN 402 - UNH Jan. 28, 1992

Note what I jotted down immediately below the diagram: “1.) this model is false (limited) because comm is only one way (linear); 2.) & assumes that sender is active & receiver is passive; & 3.) ignores the fact that sender & receiver interact w/ one another.”  Here’s what the model looks like in its original form, as published in Shannon and Weaver’s Mathematical Theory of Communication (1949, based on a paper Shannon published in 1948).

Shannon & Weaver Model of Communication, 1948/1949

Such was the lesson from day one of just about every communication theory course I subsequently took and, later on, taught.  Shannon and Weaver were wrong.  They were scientists who didn’t understand people, much less how we communicate.  They reduced communication to a mere instrument and, in the process, stripped it of its deeply humane, world-building dimensions.  In graduate school I discovered that if you really wanted to pull the rug out from under another communication scholar’s work, you accused them of premising their argument on the Shannon and Weaver model.  It was the ultimate trump-card.

So the upshot was, Shannon and Weaver’s view of communication was worth lingering on only long enough to reject it.  Twenty years later, I see something more compelling in it.

A couple of things started me down this path.  Several years ago I read Tiziana Terranova’s wonderful book Network Culture: Politics for the Information Age (Pluto Press, 2004), which contains an extended reflection on Shannon and Weaver’s work.  Most importantly she takes it seriously, thinking through its relevance to contemporary information ecosystems.  Second, I happened across an article in the July 2010 issue of Wired magazine called “Sergey’s Search,” about Google co-founder Sergey Brin’s use of big data to find a cure for Parkinson’s Disease, for which he is genetically predisposed.  This passage in particular made me sit up and take notice:

In epidemiology, this is known as syndromic surveillance, and it usually involves checking drugstores for purchases of cold medicines, doctor’s offices for diagnoses, and so forth. But because acquiring timely data can be difficult, syndromic surveillance has always worked better in theory than in practice. By looking at search queries, though, Google researchers were able to analyze data in near real time. Indeed, Flu Trends can point to a potential flu outbreak two weeks faster than the CDC’s conventional methods, with comparable accuracy. “It’s amazing that you can get that kind of signal out of very noisy data,” Brin says. “It just goes to show that when you apply our newfound computational power to large amounts of data—and sometimes it’s not perfect data—it can be very powerful.” The same, Brin argues, would hold with patient histories. “Even if any given individual’s information is not of that great quality, the quantity can make a big difference. Patterns can emerge.”

Here was my aha! moment.  A Google search initiates a process of filtering the web, which, according to Brin, starts out as a thick soup of noisy data.  Its algorithms ferret out the signal amid all this noise, probabilistically, yielding the rank-ordered results you end up seeing on screen.

It’s textbook Shannon and Weaver.  And here it is, at the heart of a service that handles three billion searches per day — which is to say nothing of Google’s numerous other products, let alone those of its competitors, that behave accordingly.

So how was it, I wondered, that my discipline, Communication Studies, could have so completely missed the boat on this?  Why do we persist in dismissing the Shannon and Weaver model, when it’s had such uptake in and application to the real world?

The answer has to do with how one understands the purposes of theory.  Should theory provide a framework for understanding how the world actually works?  Or should it help people to think differently about their world and how it could work?  James Carey puts it more eloquently in Communication as Culture: Essays on Media and Society: “Models of communication are…not merely representations of communication but representations for communication: templates that guide, unavailing or not, concrete processes of human interaction, mass and interpersonal” (p. 32).

The genius of Shanon’s original paper from 1948 and its subsequent popularization by Weaver lies in many things, among them, their having formulated a model of communication located on the threshold of these two understandings of theory.  As a scientist Shannon surely felt accountable to the empirical world, and his work reflects that.  Yet, it also seems clear that Shannon and Weaver’s work has, over the last 60 years or so, taken on a life of its own, feeding back into the reality they first set about describing.  Shannon and Weaver didn’t merely model the world; they ended up enlarging it, changing it, and making it over in the image of their research.

And this is why, twenty years ago, I was taught to reject their thinking.  My colleagues in Communication Studies believed Shannon and Weaver were trying to model communication as it really existed.  Maybe they were.  But what they were also doing was pointing in the direction of a nascent way of conceptualizing communication, one that’s had more practical uptake than any comparable framework Communication Studies has thus far managed to produce.

Of course, in 1992 the World Wide Web was still in its infancy; Sergey Brin and Larry Page were, like me, just starting college; and Google wouldn’t appear on the scene for another six years.  I can’t blame Professor W—- for misinterpreting the Shannon and Weaver model.  If anything, all I can do is say “thank you” to her for introducing me to ideas so rich that I’ve wrestled with them for two decades.

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2 comments

  1. Just discovered this site as I was researching some additional background on Claude Shannon. I actually use this model when I talk to speechwriters about how to create more compelling and effective speeches and liken back to Shannon’s work on radio signals. He doesn’t provide the feedback loop but the model turns out to be a very effective visual aid and tool for speechwriters because of the introduction of noise into the system. Part of our greatest challenge is to reduce the so-called noise in our speeches (biases of our speakers toward the audience, long sentences, unfamiliar words, poor structure, etc) that prevent the message from being heard and interpreted the way the speaker intended. So much of what we speechwriters do can rest back on this model that I build entire presentations around it. Just thought you might enjoy a different (albeit simple) view not based on print – but oral – communication. (Plus, since Shannon was a Michigander and I’m currently headquartered in Michigan, it gives me a natural storytelling hook at the very beginning, another noise reducer!) Thanks for the site. I look forward to exploring it further.

  2. Book Signal and Publishing Noise…

    bookstore by Евгений Малолетка (cyberpunk)) on 500px.com Reading Ted Striphas’ blog entry from last February, The Shannon and Weaver Model brings to mind another one of Shannon’s contributions to information theory, and one that I find appl…

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