Firstly, let me clarify, I’m not a mathematician or a physicist, I’m a marketer who has a side interest in science (closet geek). The following post derives from my belief (yes, belief, I can’t actually quantify this) that a certain element of hubris has taken hold in the tech community, driven by the genuine incredibleness that is Big Data.
A couple of centuries or so ago, following the development of Newtonian physics, humans got it into their heads that it should be possible, given the right grasp of the variables, to predict the future using mathematics. The Enlightenment brought with it the entrenchment of scientific Determinism, a belief that took a couple more centuries to shake (thank you Chaos Theory).
Looking at it in hindsight, we know was an act of hubris, but at the time it seemed so possible, science was learning ever more about the world around us and it seemed to be so predictable… if you could work out the orbits of the planets and predict eclipses, why not the weather given the right computing horsepower? Unfortunately. It never quite worked out that way – there were just too many variables for some things and the Uncertainty Principle derived out of the other area of physics – Quantum Mechanics – confirmed that for us.
Today with the growth of Big Data we seem to have developed a modern version of this hubris – the belief that if we have the right algorithm we can measure things like social influence. This seems to be driven primary by marketing folks such as myself who want to figure out ever more so our marketing dollars are used with maximum efficiency – if we can identify key influencers they can do our job via word of mouth. And on the surface it all seems so… possible! We’d like to think that from all this data we can somehow develop a complete picture, to know everything about who is who, and how they influence others through the analysis of data. But it is my belief that this is just not possible, there are too many variables. Sure we can get a general picture of things (as we can with the weather and other complex systems), but as we add more data, things become ever more variable. Witness the problems of Klout… the more detailed their algorithm becomes, the more errors it throws up (I tweeted once about the EU and I became an influencer on “Europe” – seriously).
At its heart, the basic problem behind these efforts is the premise itself – you cannot measure social media influence solely through data collected through online interaction, as you miss the far more important side of things which is real world influence. If I look through my (rather thin) collection of Twitter followers and those I follow, most of those people are ones I have met or heard about through offline contact… in fact I mentally up-weight their influence based our real world interactions. I’m fairly certain I’m not the only person who does this, it’s instinctive. So many important, yet difficult to measure ‘human’ aspects come into play – not the least elements of human instinct. How on earth can you measure that?
Naturally this will upset marketers who are seeking to identify social media influencers. As a marketer myself I can see why you do it, but I feel compelled to inform those from my industry who try, that in many ways they’re kidding themselves and relying on a number in place of a degree of instinct (a very important aspect of good marketing) as well as courage (in my books even more important, taking calculated risks is what leads to the best campaigns). It will also upset those who’s Klout score or number of Twitter followers is a source of pride. I’m sorry to say it, but there are just some things that can’t be defined by a single number.
When it comes to the interactions between humans, fortunately, the old aphorism holds true:
“Not all that can be measured matters, and not all that matters can be measured.”
Personally I think things are better that way.