Communication Models can be divided into three broad groups
- Linear Communication Models
- Starting with Aristotle and going all the way through Shannon-Weaver.
- One-Way – Source to Receiver.
- Shannon added “Noise” to the Model.
- Interactive Communication Models
- Two-Way, but only 1 iteration.
- Added “Feedback to the Model.
- Transactional Communication Models
- Two-Way but adds more than 1 iteration to the model.
- Adds “Fractal Thinking” to the Model.
Linear Communication Models
Aristotle – 300 BCE
The first communication model (that I can find) is by Aristotle.
There are a couple of different ways to look at Aristotle’s Communication Model.
Aristotle proposed his communication model around 300 BCE.
His model is more focused on public speaking than interpersonal communication. This makes perfect sense given the time he was writing. To Aristotle, the receiver was just a “passive” vessel to be filled by the eloquence and persuasiveness of the speaker.
Democracy was a new thing and being able to persuade others to your point of view was crucial for success in those early Greek City States.
Aristotle’s Model of Communication is formed with 5 basic elements:
- Speaker
- Speech
- Occasion
- Audience
- Effect.
Aristotle advises speakers to build different speeches for different audiences at different times (occasions) and for different effects.
In essence, every speech would be unique, since every audience and every time is different.
Example:
Alexander gave a speech to his soldiers before the battle at the City of Issus to defeat the Persian Empire.
Speaker – Alexander
Speech – about his invasion
Occasion – Battle for Issus
Audience – Soldiers
Effect – To defeat Persia
Or a more current example might be the President’s “State of the Union” Speech.
Speaker – The President of the US
Speech – About the way the President sees The United States
Occasion – A required address to the Joint Congress
Audience – The United States People
Effect – To enact the President’s Policies.
Shannon & Weaver – 1948
Systematic empirical research on communication began in the 20th Century, inspired by the technical improvements to wireless and wired networks during the World Wars.
One man stood out in the development of the next Model of Communication – Claude Shannon.
Claude Shannon took Aristotle’s model and added an important element – Noise.
(Noise means obstacles in the communication process. Noise refers to any interference in the channel or distortion of the message.)
A couple of things to notice in Shannon’s Model of Communication:
- Notice that Shannon only includes “Noise” in the “Channel.”
- This makes sense because Shannon worked for AT&T. He was mostly concerned with Noise in the AT&T Network.
- However, it didn’t take long to realize that Noise exists in every element of the Communication Model.
- Shannon added Concepts like Entropy and Redundancy.
- By Including Entropy, Shannon offered a way to measure information as the “Reduction of Uncertainty.”
- By Including Redundancy Shannon offered a way to reduce noise by increasing redundancy.
Linear Models are fairly simple models in which a message is simply passed from sender to receiver.
While the linear model was highly influential during the mid-20th century, this model is too simple for today’s use.
Its limitations are easy to see if you pause to think about the beliefs about communication, or assumptions, made in this model.
A Linear Model assumes that communication only goes in one direction.
Here, a person can be a sender or receiver, but not both.
This is problematic because communication in action is more dynamic than the linear model suggests.
In real life, communication involves a give-and-take between senders and receivers.
Listeners are not simply passive receptacles for a sender’s message.
It is said that one cannot “Never” communicate. Even not saying anything is communication.
A Linear Model is limited because it provides only one channel for only one message at one time.
The reality is that we receive many messages on many channels simultaneously.
A Linear Model implies that messages themselves are clear-cut with a distinct beginning and a distinct end.
The reality is, at least with human communication, messages most often build on one another.
Communication is rarely, if ever, as neat and tidy as a linear model would suggest.
Hence the need for a better model.
So, it is not surprising the next evolution in Communication Models was the “Interactive Communication Model.”
Interactive Communication Models
In the move to a more dynamic view of communication, Interactive Communication Models add another channel, in which communication and feedback flow back to the communication “Initiator”.
In addition to the 2nd communication channel added, the Interactive Communication Models add Feedback.
- Feedback is the new term added to the Interactive Communication Model.
- Feedback is the response the receiver gives to a sender.
- Feedback can be verbal (i.e. “yes”) or nonverbal (i.e. a nod or smile).
- Most importantly, feedback indicates comprehension. It helps senders know if their message was received and understood.
In networking, there are specific terms “ACK” (positive Acknowledgment), “NAK or “NACK” (negative acknowledgment). This is a signal passed between communicating entities (or devices) to signify either acknowledgment or receipt of the message, rejection of a previously received message, or indicating some kind of error.
Acknowledgments and negative acknowledgments inform a sender of the receiver’s state so that the sender can adjust its own state accordingly, if desired.
By focusing on flow and feedback, interactional models view communication as an ongoing process.
One notable feature of these models is the move away from terms like “senders” and “receivers” and toward using terms like communicators, actors, or “initiators.
This implies that communication is achieved as people both send and receive messages.
Transactional Communication Models
Fundamentally, this model views communication as a transaction.
In other words, communication is a cooperative activity in which communicators co-create the process, outcome, and effectiveness of the interaction.
In the Linear model in which meaning is sent from one person to another, there is only 1 iteration. Once the receiver decodes the message the communication is completed.
In the Interactional model, there are 2 iterations, Sender to Receiver, and then Feedback from the Receiver to the Sender.
In the Transactional Communication Model, people create shared meaning in a more dynamic process. And there can be any number of iterations.
This model also places more emphasis on the field of experience.
The Transactional Communication Model sees Communication as an “ongoing” process with no specific Start or Stop.
While each communicator has a unique field of experience, they must also inhabit a shared field of experience.
In other words, communicators must share at least some degree of overlap in culture, language, or environment if people are to communicate at all.
This model also recognizes that messages will influence the responses, or subsequent messages, produced in the communication interaction.
This means that messages do not stand alone, but instead are interrelated.
The principle of interrelation states that messages are connected to and build upon one another.
The transactional model forms the basis for much communication theory because:
– People are viewed as dynamic communicators rather than simple senders or receivers
– There must be some overlap in fields of experience in order to build shared meaning
– Messages are interdependent.
Fractal Communication Model
In the 1960s Benoit Mandelbrot developed a cohesive “fractal theory.”
Fractals provide a predictive model of iterative stability.
Here is the Mandelbrot Set formula:
f(c) = Z2+ c
By using “Feedback” as the “f(c)” function, the efficiency of communication as the “Z2” variable, and the initial starting point of the communication as the “c” variable, Communication fits nicely into Fractal thinking.
Here is the result.
Fractal Communication Formula
f(e) = eC((t+i)-n) + Starting Point
f = Feedback, Fractal, Function
e = Efficiency as measured by the distance to the Endpoint (or Goal)
C = Communication = ((T+S)-N) – ((Technical Value of the Communication + Information Value of the Communication) – Noise)
In words this would be:
“Fractals” describe the chances of reaching our goals
Reaching our Goals are dependent on our Communication Efficiency.
Our Communication Efficiency is based on our ability to maximize the technical and informational aspects of communication and minimize the noise in our communication.
In a perfect world, every communication act – “iteration” – would move us closer to the end goal.
After every iteration, the question would be: Have we moved closer or further from the goal?
The efficiency of the power of Communication could be “positive or “negative.” In a positive efficiency, the iteration takes us closer to the goal. In a negative efficiency, the iteration takes us further from the goal.
Communication is based on the interaction between, technical communication -bandwidth -, Informational communication – shared code -, and Noise.
This fractal formula for Communication uses the formulas developed by Claude Shannon in his work on the “The Mathematical Theory of Communication. “