Thursday, February 07, 2008

how long is a piece of string? (and who does it join?)

So the recent posts by Gav & Katie have mingled in my brain with the SNA work I have been doing.

Trad market research is based demographics. Although it lumps people together in groups (by age, location, wealth, gender, race, etc), it tells us little about how they interact with each other.

As Gav well knows, audience 2.0 isn't really an audience. An audience sits in the dark, only joined to each other by what they observe. This audience is noisy, they jump out of their seats. They interrupt the play. The critical thing about social media is that it's, well, social. What you have is more like a football terrace or a dance hall than a theatre/cinema/TV audience.

In SNA, you have two sets of measures:
  1. Attributes of nodes - i.e. characteristics of entities or demographics if we're talking about people (which we may not be).
  2. Attributes of links between nodes. Now a link between nodes is simply an interaction between them. We might have edited the same wiki page, we might communication in some fashion once a week about tennis, we might be having sex every night.

As a network analyst, you are often concerned with the interplay between node & link data - e.g. do 20-something males talk to more people more frequently on the topic of, say, organisational change. Or aftershave.

Link data is normally collected in 2 ways:

  • Surveys of network participants - with all the problems of surveys (e.g. deliberate lying, wishful thinking, inaccurate recall).
  • Automated collection of data (e.g. email usage patterns). In absolute terms, these are more reliable but give you no access to subjective evaluations of interactions - e.g. "that email was useful for me".

If we are going to understand the social media environment we need a solid understanding of 2. as well 1. There are several impediments to this:

  • Collecting link data has traditionally been a lot harder than demographic data.
  • Link data that is easy to collect is often difficult to interpret ("was that email exchange positive or negative?").
  • Network-based metrics are poorly understood by marketers (in fact, by everyone).
  • SNAs have tended to break down when you get more than 200+ participants - which in the consumer space is piddling. There are ways round this however.

Understanding social media and herd behaviour requires us to revolutionize our measurement techniques. Are we ready for that?

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