FeedWinnower: layering structures over collections of information streams

Authors:
Lichan Hong;Gregorio Convertino;Bongwon Suh;Ed H. Chi;Sanjay Kairam
Affiliations:
Palo Alto Research Center (PARC), Palo Alto, CA, USA;Palo Alto Research Center (PARC), Palo Alto, CA, USA;Palo Alto Research Center (PARC), Palo Alto, CA, USA;Palo Alto Research Center (PARC), Palo Alto, CA, USA;Palo Alto Research Center (PARC), Palo Alto, CA, USA
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2010

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Abstract

Information overload is a growing threat to the productivity of today's knowledge workers, who need to keep track of multiple streams of information from various sources. RSS feed readers are a popular choice for syndicating 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 (topic, people, source, and time), thus facilitating feed triage. The combination of the 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.