Software

Traditionally, social networks use explicit relationships between individuals rather than attribute data, thus not exploiting the affinities among individuals. Yet, the affinities that tie individuals together offer unique opportunities to discover new social networks and track community evolution. We propose the idea of Implicit Affinity Networks (IANs) to build communities that can be visualized and tracked.

To further this research, we have created a new Web community that captures the dynamic nature of individuals. Participation in the community consists simply of describing yourself, however you wish to, through time. We ask that users come at least twice during the next three months to ensure that their profiles are up-to-date.

We extend an open invitation to all that are willing to participate at:

http://dml.cs.byu.edu/IAN/register/

Preliminary results have been submitted for publication. All results will be made freely available.

Matt Smith
dml.cs.byu.edu/~smitty