Monday, June 02, 2008

About networks of resources and users

This visualisation is to explore the networks of users that form between resources that are shared in collections. I think this is one of the most interesting visualisations of the dataset, and the one that inspires me the most.

Same as before, click to interact within the image, or if you click on the title on top of the image, you can get the network in a bigger window.


What's there? It's a network diagram where the nodes represent users (user id number) and the edges are the names of learning resources that these users have saved in their collections.


You can zoom into the diagram and explore it. Same as with the previous post, we can see that lots of the resources that users have put in their collections are not shared with other users. These are the singletons that are not part of the common network here.

Then, there are some star like structures that can be found. Like this one. Here the resource highlighted is something that both users (user 59 and 155) had added into their collection.

What I think, I would almost bet on, is that if these users were made aware that they share this resource in their collections, they would be interested in looking at what other resources are in the other person's collection. In this case the user 59 could be interested in looking at the collection of the user 155 has put in her collection.

This basically would be the idea of making underlying social networks visible in a repository to allow social navigation of like-minded users collections. Or, if you wish, a recommender could take advantage of these underlying connections as well. For the recommender, though, the data is very sparse, as can be seen from the visualisation. For that reason, I think we first should explore social navigation possibilities, and then launch for recommenders, when we get more data.

These resources that connect users, or in some cases (hopefully one day) even communities together, are valuable stuff. I have previously referred to this as one way to identify learning resources that cross borders easily. In this case, the two communities could be speaking different languages or be from different countries.

Some suggested that these objects could be also boundary objects. I cannot get my hands on the original article now (frustration of working from home!), so I am referencing some others that reference it:
Star (1989) and Star and Griesemer (1989), on the other hand, are concerned with the distribution of artefacts across communities. Boundary objects are artefacts used by communities: they cross the boundaries between communities and retain their structure, but are interpreted differently by them. The notion of boundary objects was developed by Star (1989) and Star and Griesemer (1989) as a way to explain co-ordination work between communities.
In a larger sense, maybe some of them could be boundary objects. I will need to think about this more..

Anyway, here is another little visulaisation that is actually an overview of the resources that users have saved in their collections. You can visualise it in many ways, you the ordering function on the top.




Star, S. L. 1989. The structure of ill-structured solutions: boundary objects and heterogeneous distributed problem solving. In Distributed Artificial intelligence (Vol. 2), M. Huhns, Ed. Morgan Kaufmann Publishers, San Francisco, CA, 37-54.

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