This capstone report analyzes how user-generated metadata can enhance findability in social software applications like content tagging and recommender systems. The report examines these systems' strengths and weaknesses for information classification, retrieval, and discovery. Based on an analysis of six system-factor combinations, the report finds that content tagging systems have stronger overall findability than recommender systems, particularly for information classification. However, recommender systems exhibit strengths for information discovery. The report provides examples of content tagging and recommender systems to illustrate different design approaches.

1. Capstone Report Presentation User-Generated Metadata in Social Software: An Analysis of Findability in Content Tagging and Recommender Systems Presented by Michael Barnes In partial fulfillment of the requirement for the degree of Master of Science. March, 2007

7. TIME-liness of Topic Since then, the rise of social software designed to leverage user-generated metadata has boomed. The 2006 Time Magazine’s “Person of the Year” was - the user! The rapid increase of user participation and user generated content in social software systems continues to gain popularity under the moniker of “Web 2.0.”

8. TIME-liness of Topic “ It's a story about community and collaboration on a scale never seen before. It's about the many wresting power from the few and helping one another for nothing and how that will not only change the world, but also change the way the world changes. It's a tool for bringing together the small contributions of millions of people and making them matter. And for seizing the reins of the global media, for founding and framing the new digital democracy, for working for nothing and beating the pros at their own game, TIME's Person of the Year for 2006 is you.”

31. Recommender System Example