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Group Relationship Management

group.jpgIn 1997 I wrote about a "nodal politics", a network-based alternative to the centralized, top-down efforts that have traditionally used members or supporters as sources of contribution and political power-through-numbers without empowering them to do actual political work. The Internet, a network of networks, seemed to present a model for organizing could be decentralized and, as Jillaine Smith, Marty Kearns, and Allison Fine noted recently, could push power to the edges. I had envisioned a network of groups and individuals that would share information and form ad hoc coalitions, but vision is one thing – making it work is another.

Recently my friends at CivicSpace Labs were talking about needing an API for groups, and I was thinking we need to define and understand social as well as technical group interfaces in the context of an evolving network society. There are projects focused on individual identity (Identity Commons, Identity Metasystem) and constituent relationship management (or relationship of the group to the individual, e.g. CiviCRM), but I'd looking for work on the relationship of groups to other groups as well as to individuals.

While taking a walk yesterday I sorted out some initial thoughts about a concept of Group Relationship Management. Some basic first thoughts:

Assumptions about individual and group networks:

  • Individuals and groups are nodes in a network.
  • Individuals connect to one or more individuals, and one or more groups.
  • Groups connect to one or more individuals, and one or more groups.
  • Groups include one or more individuals, formally or informally organized. (Organization is a primary defining characteristic of "group" in this context.)
  • Individuals that connect to many individuals are hubs in a network of individuals..
  • Groups that connect to many groups are hubs in a network of groups. (I don't think the group/individual relationship, i.e. how many individuals are in a group, is relevant in this context, though an individual group member may be the source of the connection to another group).

The problems we most want to solve:

  • Discovery: how do groups and individuals find other groups and individuals that share affinity and are potential partners in ad hoc or sustained coalitions.
  • How do groups share data about individuals, and how is data sharing constrained by privacy issues?

posted this at 12:03 PM
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Jon wrote:


The problems we most want to solve:

  • Discovery: how do groups and individuals find other groups and individual that share affinity and are potential partners in ad hoc or sustained coalitions.

  • How do groups share data about individuals, and how is data sharing constrained by privacy issues?


Discovery is an interesting problem, and one that has several possible approaches/solutions.

  • You can try using a typical search but that often reveals irrelevant or spammy results, not people and groups.

  • Another way is start blogging about your areas of interest and affinities, and tag your posts with the areas, topics etc. Then check tag aggregation pages to see who else is blogging about such topics.

  • A third way to connect with people and groups that share affinities, is to blog and hyperlink to their sites, blogs, and blog posts. If you are inspired by these other people, hyperlink to them with the XFN rel="me" value which will let those folks know that you're inspired by their work. Then when they check their XHTML Friends Network using XFN search engines like RubHub or XHTML Friends.net, they'll discover you too.

As for publishing and sharing information about yourself and other people, hCard is perfect for that. And remember to always respect people's privacy, and only publish information that you (and the other people involved) are perfectly ok with making public on the web.

How about creating sites that are clearing houses for such information?

Places where people know to go for definitive listings.

That's one element of what I am trying to do :-)

Clearinghouses would also benefit from some standard, machine-readable way of presenting data for discovery, which is what I had in mind. Tantek's suggestion - the hcard standard - works for individuals... could it be extended to groups? And might it be better to use XRI? (See http://en.wikipedia.org/wiki/XRI#Examples)

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