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Exploring patterns of social commonality among file directories at work
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Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems table of contents
San Jose, California, USA
SESSION: Collaboration at work table of contents
Pages: 951 - 960  
Year of Publication: 2007
ISBN:978-1-59593-593-9
Authors
John C. Tang  IBM Research, San Jose, CA
Clemens Drews  IBM Research, San Jose, CA
Mark Smith  IBM Research, San Jose, CA
Fei Wu  University of Washington, Seattle, WA
Alison Sue  IBM Research, San Jose, CA
Tessa Lau  IBM Research, San Jose, CA
Sponsors
ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 13,   Downloads (12 Months): 104,   Citation Count: 5
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ABSTRACT

We studied files stored by members of a work organization for patterns of social commonality. Discovering identical or similar documents, applications, developer libraries, or other files may suggest shared interests or experience among users. Examining actual file data revealed a number of individual and aggregate practices around file storage. For example, pairs of users typically have many (over 13,000) files in common. A prototype called LiveWire exploits this commonality to make file backup and restore more efficient for a work organization. We removed commonly shared files and focused on specific filetypes that represent user activity to find more meaningful files in common. The Consolidarity project explores how patterns of file commonality could encourage social networking in an organizational context. Mechanisms for addressing the privacy concerns raised by this approach are discussed.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Amazon, "Online Shopping for Electronics, Apparel, Computers, Books, DVDs & more", http://amazon.com/ (verified January 17, 2007).
 
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del.icio.us, "del.icio.us/about", http://del.icio.us/about/, (verified January 17, 2007).
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6
7
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9
 
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Google Desktop, "Google Desktop ---- Features", http://desktop.google.com/about.html (verified January 17, 2007).
 
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Gmail, "About Gmail", http://mail.google.com/mail/help/about.html (verified, January 17, 2007).
 
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Haythornthwaite, Caroline, "Social network analysis: an approach and technique for studying information exchange", Library & Information Science Research, Vol. 18, No. 4, 1996, pp. 323--342.
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"RFC 1321", http://rfc.net/rfc1321.html, (verified January 17, 2007).
 
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Rabin, M. O., "Fingerprinting by Random Polynomicals", Report TR-15-81, Center for Research in Computing Technology, Harvard University, 1981.
 
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Collaborative Colleagues:
John C. Tang: colleagues
Clemens Drews: colleagues
Mark Smith: colleagues
Fei Wu: colleagues
Alison Sue: colleagues
Tessa Lau: colleagues