The media + communication studies network
The Relationship between Language and Communication [ii]
The Mathematical Theory of Communication
(Shannon and Weaver)
Continuing the discussion on the relationship between language and communication initiated in my earlier blog post, we will now discuss another interesting model of communication, which unlike Semiology (which was discussed in the previous blog) deals principally with the message source, the channel, the message receiver and the element of noise.
According to Shannon, American mathematician and electrical engineer, there are two ways of sending and receiving information, namely, discrete signals and continuous signals. The letters of the English language are considered discrete signals while analog signals like sound are continuous signals.
Information, according to this theory, is measured by randomness in the choice of words (signs or symbols) used for constructing the message (because of the freedom of choice we have in constructing messages). This theory uses the following simple mathematical calculation for measuring the information contained in a message:
After calculating the actual randomness of the choice of words (signs or symbols) used by a particular source we compare it to the maximum possible value. This ratio of the actual number of words used to the maximum possible is called the relative entropy. If this figure is 9 then it means that the source is 90% free to form a message with the same symbols. One minus the relative entropy is called the redundancy.
This (redundancy) is the fraction of the structure of the message, which is determined not by the free choice of the sender, but rather by the accepted statistical rules governing the use of the words (signs & symbols) used in the message. This part of the message is redundant or unnecessary because the message would be essentially complete even without it.
The redundancy of the English language is about 50 per cent. [1] Thus, about half of the letters or words we choose to express ourselves are of our free choice, while the other half are really controlled by the statistical structure (grammar) of the language. Which means, about half of the words out of the basic 3500 required to communicate effectively in the English language (refer previous blog post) are redundant and one can communicate effectively with the help of just about 1750 words!
Further, according to this model, the amount of information contained in a message is directly proportional to the amount of freedom of choice in selecting the words that constitute the message; but, paradoxically, corresponding levels of uncertainty accompany levels of freedom. Now, if noise is introduced in the message, it will automatically increase the uncertainty, which in turn will lead to the corresponding increase in the perception of the information content of the message (as explained above).
The result of this mathematical relationship between the amount of information included in the message and the freedom of choice is that distorted messages appear to be informative. In fact, the more distorted a message, the more informative it will seem.
It seems from this theory that it is impossible to construct accurate messages and eliminate noise; which, in fact, can creep in at any point during the communication process. This theory is simple and appealing even though the terms ‘information’ and ‘uncertainty’ are given a positive correlation. However, it is important to note that ‘information’, as mentioned here, is a measure of one’s freedom of choice in selecting a message.[2]
Like Semiology, the Mathematical Theory of Communication, or Information Theory, too highlights the improbability of accurate communication. It is particularly interesting to note that 'noise' actually creates the illusion that a message is informative.
If we add to this the conclusions drawn from the review of theories of Semiology (discussed in the previous blog), then we can imagine how difficult it is to rely on ‘language’ for communication effectiveness. Consequently, the following pertinent questions arise:
(1) When we feel that a lot of information has been received are we accurate in our perception or have we just received noise?
(2) Given our perceptual blindness how can we differentiate between the usable information received and the useless 'noise'?
(3) If noise can be perceived as information then is it possible that most of us regularly transmit noise while being under the impression that we are transmitting useful information?
For a student of communication these questions are both exciting and exasperating. It seems like a lot of distance must be traveled before the answers to these questions can be sighted. And yes, if you found this blog post informative it is possible that this is only a highly distorted message :).
In my next blog post we will discuss how gender affects interpersonal communication.
[1]George N. Gordon, Emeritus Professor of Communications, Fordham University, Bronx, New York, Redundancy, Communication, Encyclopedia Britannica Inc.,2005, CDROM
[2] Shannon, C. E. A Mathematical Theory of Communication. Bell System Technical Journal, vol. 27, pp. 379-423 and 623-656, July and October, 1948. &
D. Slepian, editor, Key Papers in the Development of Information Theory, New York: IEEE press, 1974.
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