Information Theory
of Claude Shannon & Warren Weaver
By: Shane Paris
Information Theory was first developed by Claude Shannon and Warren Weaver around the late 1940's.
Shannon, a research scientist with Bell Telephone Company, and Weaver, a consultant with the Rockefeller Foundation collaborated to devise
a theory that explained the components and processes involved in interpersonal communication. The underlying theme was
that to increase the content of information you must reduce entropy. To help explain this theory, Shannon and
Weaver devised a linear model of communication which diagramed the communication process between two individuals. In this model,
they created a information source, a transmitter, a reveiver, a destination, and finally noise. In interpersonal communication,
you and the person with whom you are communicating with would serve as the information source, and the destination respectively.
Your voice and the other person's hearing would account for the transmitter and the receiver. Then the noise would be
anything that caused interference with the communication process.
For example, let's say that you were carrying on a conversation with your friend when all of a sudden, you spot a voluptuous
women approaching your way which in turn, breaks your train of thought.
In this example the communication process between the two individuals is complicated with the introduction of noise. Here the noise
occurs because the individual becomes distracted as a result of the women. The noise acts to block the flow of information from
the transmitter to the receiver. In order for the message to successfully be delivered the information must exceed the amount
of noise. If the individuals want to communicate their message they must retransmit the information with less noise.
This web page will serve as a stepping stone to provide you with an introduction into the world of Information Theory.
Key Concepts of Information Theory
Combat entropy bit by bit.
Channel Capacity = Information + Noise
Information - The reduction of uncertainty.
Entropy - Disorganization or chaos in a system.
Noise - Anything that interferes with the message.
Linear Model of Communication
Information Theory Links
To view a research report by Sara click here
To view a research report by Tara click here
To view an application by Angela click here
To view an application by Kevin click here
To view a critique by Kyle click here
To view additional Information Theory Links click here
To view a theory that applies some of the same elements as Information Theory check out Karl Weick's
Information Systems Theory
This page was last updated by Shane Paris on March 14, 2000