Buzzer - Online real-time topical news article and source recommender

Abstract

With the increasing growth of online communication tools, as well as consumption of topical and current information from the web, there is a growing difficulty for users to keep abreast of current, relevant and interesting material. The widespread online adoption of techniques such as recommender systems has come about due to their proven ability to reduce and personalise the constituents of the information explosion. The collective conversations found on such services as Twitter are playing an increasingly useful role in monitoring current and topical trends among a large set of culturally and geographically diverse users. In this paper, we describe the ongoing development of a system that harnesses real-time micro-blogging activity such as Twitter, as a basis for promoting and influencing personalized online news and blog content. The system provides a real-time way for users to engage with content that has been influenced by popular activity of both the global community, or their own friends. We also discuss some preliminary results based on a live user evaluation. © 2010 Springer-Verlag.