Harnessing Wisdom of the Crowds Dynamics for Time-dependent Reputation and Ranking

Abstract

The “wisdom of the crowds” is a concept used to describe the utility of harnessing group behaviour, where user opinion evolves over time and the opinion of the masses collectively demonstrates wisdom. Web 2.0 is a new medium where users are not just consumers, but are also contributors. By contributing content to the system, users become part of the network and relationships between users and content can be derived. Example applications are collaborative bookmarking networks such as dcl.icio.us and file sharing applications such as You Tube and Fliekr. These networks rely on user contributed content, described and classified using tags. The wealth of user generated content can be hard to navigate and search due to difficulties in comparing documents with similar tags and the application of traditional information retrieval scoring techniques are limited. Evaluating the time evolving interests of users may be used to derive quality of content. In this chapter, we explore a technique to rank documents based on reputation. The reputation is a combination of the number of bookmarkers, the reputation of the bookmarking user and the time dynamics of the document. Additionally, this reputation measure is extended to take into account the time-dependent, term-dependent reputation of a document. Experimental results and analysis are presented on a large collaborative IBM bookmarking network called Dogear.