Shannon-Weaver: Physical noise

Shannon is generally considered to have been primarily concerned with physical (or ‘mechanical’ or ‘engineering’) noise in the channel, i.e. unexplained variation in a communication channel or random error in the transmission of information. Everyday examples of physical noise are:

  • A loud motorbike roaring while you are trying to hold a conversation.
  • Your little brother standing in front of the TV set
  • Mist on the inside of the windscreen
  • Smudges on a printed page
  • Snow on a TV set

It might seem odd to use the word noise in this way, unless perhaps you’re a hi-fi buff, in which case you’ll be familiar with looking up the claimed ‘signal-to-noise ratio’ for the various bits of equipment you buy. In this technical sense, ‘noise’ is not necessarily audible. Thus a TV technician might speak of a ‘noisy picture’. Generally speaking, in this kind of everyday communication, we’re fairly good at avoiding physical noise: we shout when the motorbike goes past; you clout your little brother; cars have demisters.

However, it is possible for a message to be distorted by channel overload. Channel overload is not due to any noise source, but rather to the channel capacity being exceeded. You may come across that at a party where you are holding a conversation amidst lots of others going on around you or, perhaps, in a Communication lesson where everyone has split into small groups for discussion or simulations. Shannon and Weaver were primarily involved with the investigation of technological communication. Their model is perhaps more accurately referred to as a model of information theory (rather than communication theory). Consequently, their main concern was with the kind of physical (or mechanical) noise discussed above.

Although physical noise and how to avoid it is certainly a major concern of scholars of communication, the Shannon and Weaver model turns out to be particularly suggestive in the study of human communication because of its introduction of a decoding device and an encoding device. The possibility of a mismatch between the two devices raises a number of interesting questions. In technological communication: I give you a PC disk and you stick it into a Mac – the Mac can’t decode it; I give you an American NTSC video tape and you stick it into a European PAL video recorder – the recorder won’t decode it. Transfer this notion of a mismatch between the encoding and decoding devices to the study of human communication and you’re looking at what is normally referred to as semantic noise. That concept then leads us on to the study of social class, cultural background, experience, attitudes, beliefs and a whole range of other factors, which can introduce noise into communication.

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