OPEN

2 responses to “I want to play with a neural network!”

1. 

   Heather Yaxley

   October 22, 2006 at 10:24 am

   I think the predictive investigation of networks has application for Public Relations in relation to issues and crisis management. Traditional models tend to present a linear chronological approach to how an issue or crisis will develop, peak and recede. But recent crises, and the emergence of online social media and networks, must make these models redundant. Are there patterns and key dimensions that can be mapped and modelled in order to predict which issues will peak, when and how? The old way of responding by relying on the pre-determined plan in the cupboard is no longer relevant as crisis development today seems more akin to chaos theory. Any thoughts?

2. 

   Antony Mayfield

   October 22, 2006 at 10:37 am

   The first step is to understand how online networks work – and to start thinking in terms of planning for these rather than for the news-cycles we were used to when dealing simply with channel / broadcast media.

   As I’ve mentioned before, the main differences are:

   1. Scale: there’s so much more content and players: do we know what our communities of interest look like online? How do they behave and communicate when “crisis” stories break?
   2. Speed: a day seems like an age in networks. Silence is incriminating and damaging – how do we deal with that? What’s best way we can start communicating soonest without
   3. Evolving nature: you’re right to say that networks look different at different points in a news cycle. It’s reflected in the kinds of results that get to the top of search engines in a crisis. The kinds of results for “Dell laptop fire” or “Dell battery recall” were very different on day one of the crisis to two months later – we need to plan to communicate so that we meet the short and longer term needs of networks of interest around a story or subject and ensure we are producing communications and content that will be successful for both.

   In summary, networks are highly complex systems. Like the weather and economies we can study how they behave and have behaved in the past and develop theories that can be tested and help us to plan – but we need to acknowledge that we can’t predict how they will work in any given scenario with absolute certainty.

   There are many tools out there for looking at behaviours of networks and online communities. A few firms – including mine, Spannerworks – are developing ways of seeing and expressing how networks develop.