Reuters reported Oil at $64 a barrel this week which led me to think how the Relationship Value Model would be applied by governments contemplating oil shortage and production problems pushing prices towards $100.
In the first instance, landscaping the broad range of knowledge, opinion and projections by many groups is mandatory. This would need to be across many networks using an array of channels for communication.
Obviously there are the traditional news channels of the nature used in the early empirical research into the Model. There is the academic media which is slow to publish but peer reviewed and there are analyst reports, oil company reports and projections plus the work of the financial institutions.
The commentary among NGO's and unmediated commentary from sources such as Blogs, Usenet, Listserve as well as focus groups and the like may also be of help. The methodologies used will probably be automated content analysis because of its speed and consistency (I would lean towards semantic analysis where I have had considerable success in the past - see below for reference).
Using this approach, we will be able to identify the most significant concepts that are relevant to each communication channel.
Each such concept will be associated with kindred concepts and in combination one would be able to identify similarities and differences between each of the channels and the people who are presenting such views.
In addition, where concepts are presented as an explicit description (e.g. 'oil' or “global warming') we might consider such expressions as tokens and where there are concepts emerging that are semantically associated with such tokens that are implicit or metaphoric (e.g. 'shortage', 'disaster' etc.) we would have identifies values associated with such tokens.
In identifying where there are the same values and associated tokens in any channel, we can assume convergence is occurring (and the actors who have the most affinity) and, in addition, we would be able to identify where there is actual or latent convergence. In both cases, we would have identified the constituents related to the emerging topics and their concerns.
The advantage of this form of landscaping is that it would also provide a view of the 'language' of the people expressing concerns and interest which offers the communicator a lingua franca which would be attractive to and understood by these groupings.
From such information, policy making and the means by which policy can be explicated to the pubic can be made.
(Latent Semantic Analysis is developed from the work presented by S. C. Deerwester, S. T. Dumais, T. K. Landauer, G. W. Furnas, and R. A. Harshman. Indexing by latent semantic analysis. in the Journal of the American Society of Information Science 41(6):391--407, 1990
