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Dogear: Social Bookmarking in the Enterprise

CHI 2006 ProceedingsCambridge, MA, IBM

David R Millen, Jonathan Feinberg,

Bernard KerrPresented by Sharon HSIAO

2007/04/20

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Introduction• people created bookmarks based on the quality

of and personal interest in the content, high frequency of current use, and a sense of potential for future use (Abrams et al., 1998)

• del.icio.us, Yahoo’s “My Web 2.0”– Personal collections of bookmarks and instantly share

their bookmarks with others– keywords or tags– Social Nature: visible to others

• (to reorient the view by clicking on tags or user names, “pivot browsing”)

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Social Bookmarking For Enterprise

• whether large enterprises or organizations would also benefit from a social bookmarking system?

• Dogear

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Dogear• Identity and transparency

– Real-world identity• It is possible to browse the enterprise bookmark

collection anonymously (Lurking)– access control within the application

• The success of social software applications require “Critical mass” of user participation provide value to user, ensure sustainable contribution levels, vibrant interactions

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Alerting and Discovery

• RSS and Atom: every page– Individual– Tag

• Collaborative filtering techniques (plan)– Similar tags/tags combination– Similar bookmark (URL) collections– Click streams– Text analysis: titles, descriptions, comments

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• Output format• Query constraints

– HTTP GET parameter– User, tag, text

• Other state

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Field Study

• July~September, 2005• 686 individuals• 27% create bookmarks• 54% click on URL that was bookmarked• geographical diversity (70% Americas, 7%

from Asia-Pacific, and 23% Europe)• Large firm (> 300K employees) IT industry,

in software development and support

providing a social bookmarking service for enterprise (secure) web pages

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•1971 distinct tags•10 distinct tags per user•number of tags used and the number of bookmarks created•stronger than del.icio.us

< 10 bookmarks

> 10 bookmarks

r = .74 r= .5

p < .001 p < .001

over 80% of the bookmarks havethree of fewer tags

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• Social network analytical method

• systematically mine this info to automatically generate tag groupings and to alert users (plan)

30% of users general search(averaging eight search queries per user)

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• User survey– 100/233 email survey (43%

response rate)– 44% used the service at least once

a day and an additional 42% used the service weekly

– 65% self-report as expert users• find information on both the

corporate intranet and the external web

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Conclusion

• improve information sharing, expertise location and support of communities of interest within the enterprise

• improve personal bookmark management• there is a willingness to share informationa

l resources for the benefit of the organization

• meet a need for corporate social bookmarking