Network Diversity Index Redux

Thanks to Darren Draper for taking a look at a suggestion I had made for network analysis in a previous post. Hopefully this is not a breach in "blog etiquette" , but my response to his comment was rather long so I entered it as a post instead.
Here was Darren's comment:

OK, so I used the Shannon index calculator to learn that my H1 = 0.9088. But what does that mean?


I'm assuming that an H value of 1 means that your population is not diverse - at least not diverse when considering the different kinds of populations assigned (which are arbitrary and subject to bias).

Here's a screenshot of what I've entered (as you can see, I mostly use Twitter to connect with the ed-tech community). http://tinyurl.com/6lupxe

Darren, most biological communities will have a diversity index between 1.0 and 4.0. Your "community", with an index of .9088 indicates, on the surface, very little diversity. This would be what classical ecologists might call a "typal" community, like "grassland". In terms of your network, most of your information is coming from a single "species" called EdTech. Example: An established, mid-latitude ecosystem with limiting resources and most of them passing through a large number of very few or even a single species. The other species in this community, and there may be many, are represented by maybe only a single individual in the sample. You might say "Well yeah, its an EdTech community!' Low diversity in a network, to me, equates with focussed, but low quality (depth) information. Let's say you use Wordpress for your CMS, so you have a number of EdTech people using Wordpress in your network. If you added a few members of the Wordpress Codex community you might also pick-up information that may be of use to you.

Two observations:
One. If we consider this assessment to be correct, then, in conjunction with your discussion of Twitter Set Theory, you should be able to reduce the number of individuals in your network without reducing information content. Your EdTech species has a population of 257 competing for a resource, your time. Assume a 1 in 10 overlap in your EdTech set, you could effectively reduce the number of individuals in your EdTech population to 25-30, increasing efficiency and not degrading information. You might say at this point, "I've come to rely on my connection to more than 30 individuals in this group. How can I eliminate any one?" This brings me to observation two.

I believe your diversity is really higher than reported. I said "on the surface" earlier because I think the problem is in identifying a "species" in our analogy. If all the members in your EdTech population were giving you the same information, competition would have reduced their number before now (my guess is their number is growing). Case in point. Three different species of Anole lizard were observed in a certain tree of a Caribbean island. This couldn't happen because similar species couldn't occupy the same niche for very long without competition favoring one over the other two. Closer inspection revealed that each of them was occupying a very specific part of the tree and feeding on very specific prey in that area. Thus, they were not in competition with each other and were occupying a different role (niche) in the community. I believe closer scrutiny of your EdTech population will really reveal very distinct "species" exist within this group.

Biologists identify species using a key based on a dichotomy (dichotomous key). An organism is assessed as having a described character, which places it into one group or lacking that character which places it in another group. A new character is describe an the assessment continues in branching fashion until the "species" is identified (keyed out) by the set of accumulated characters. I've begun an attempt at this on a wiki but this is a developing idea much like the issue of "tagging". It will take time. One thing that might help is for people to give as much information in their profiles as they can comfortably give.

Of course, most of this is hypothetical and may be based on untested assumptions, but, if networks are going to be an important part of how we use the technology, then I think some metrics need to be established for assessing them.

Thanks again, Darren for the conversation.

technorati tags: Darren Draper, network, Twitter, diversity index,

Network as Biological Community

Recently, Alec Couros, in preparation for a presentation to his faculty, tweeted the question,"What does your network mean to you?". As a tribute to the vitality of his network, the responses (twice) produced a host of comments (collected in a Voicethread here) to answer the question.

As a self-proclaimed digital primitive, I began to answer the question with analogs to the Ecosystem component of the Biology content I teach. If the internet has become the landscape of our Personal Learning Environment (PLE), then I will employ a Synectics strategy I use with my students and create the metaphor; "Networks as biological communities."

We might define a biological community as all the interacting species within a habitat (or biotope). My learning network is a community of interacting individuals within my learning environment. Now here, I first rushed to consider that each individual member of my network would represent a different species. After a bit of mental wrangling, I realized that was incorrect. I should consider each person in my network as a member of a population which is "a group of individuals of the same species". What defines a species in this analogy and the identification of which species inhabit our "environment" will take some work. (I'm thinking a wiki may aid in this discussion).

Alec utilized the diagram above, which he had developed some time ago, as the visual for the Voicethread. Entities at the perimeter of the diagram (Web 2.0 "tools" if you pardon the expression) are ways in which other individuals in our networks perceive us and interact with us. They represent codes for who we are, thus, in the analogy, our DNA. As is true for our DNA, these codecs are able to be replicated, mutable and adaptive and in light of changes in the environment, some become more favorable than others. For example, where a web page once was the dominant form of expressing oneself, in a 2.0 environment, blogs and wikis are more favorable. Thus, blogs and wiki are selected for fitness in this environment and increase in frequency while web pages are selected against and so their frequency decreases.

This also bring in to question the definition of an interaction. What must occur in order to qualify as an interaction? Is the reading of a Tweet considered an interaction or would you have to respond to the tweet in order to qualify? Consider this, while I was unable to respond to the Voicethread directly with a comment, this blogpost was generated in response to the tweet. Some time will have to spent on categorizing the type of interactions within the network.

Why take so much time to develop the analogy this far? One, to answer the original question for myself. Two, I believe if I can fine tune the components of the analogy, there may be some ecological algorithms to develop metrics for assessing our Networks and Personal Learning Environments.

technorati tags: network, PLE, Couros, Voicethread,