Although they clearly exist, affinities among individuals are not all easily identified. Yet, they offer unique opportunities to discover new social networks, strengthen ties among individuals, and provide recommendations. We propose the idea of Implicit Affinity Networks (IANs) to build, visualize, and track affinities among groups of individuals. IANs are simple, interactive graphical representations that users may navigate to uncover interesting patterns. This thesis describes a system supporting the construction of IANs and evaluates it in the context of family history and online communities.
College and Department
Physical and Mathematical Sciences; Computer Science
BYU ScholarsArchive Citation
Smith, Matthew Scott, "Implicit Affinity Networks" (2007). All Theses and Dissertations. 1112.
communities, social network analysis, collaboration, community evolution, affinities, family history, business intelligence, recommendation systems, computer science