FeedWinnower: layering structures over collections of information streams


Hong, L.; Convertino, G.; Suh, B.; Chi, E. H.; Kairam, S. FeedWinnower: layering structures over collections of information streams. Proceedings of the 28th International Conference on Human Factors in Computing Systems (CHI ’10); 2010 April 10-15; Atlanta, GA. NY: ACM; 2010; 947-950.


Information overload is a growing threat to the productivity of todays knowledge workers, who need to keep track of multiple streams of information from various sources. RSS feed readers are a popular choice for syndicating the information streams, but current tools tend to contribute to the overload problem instead of solving it. We introduce FeedWinnower, an enhanced feed aggregator that helps readers to filter feed items by four facets (namely topic, people, source, and time), thus facilitating feed triage. The combination of these four facets provides a powerful way for users to slice and dice their personal feeds. In addition, we present a formative evaluation of the prototype conducted with 15 knowledge workers in two different organizations.

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