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Lurker demographics: counting the silent
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Source Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems table of contents
The Hague, The Netherlands
Pages: 73 - 80  
Year of Publication: 2000
ISBN:1-58113-216-6
Authors
Blair Nonnecke  Dept. of Information Systems, 1000 Hilltop Circle, Baltimore, MD
Jenny Preece  Dept. of Information Systems, 1000 Hilltop Circle, Baltimore, MD
Sponsor
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 38,   Downloads (12 Months): 148,   Citation Count: 44
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ABSTRACT

As online groups grow in number and type, understanding lurking is becoming increasingly important. Recent reports indicate that lurkers make up over 90% of online groups, yet little is known about them.

This paper presents a demographic study of lurking in email-based discussion lists (DLs) with an emphasis on health and software-support DLs. Four primary questions are examined. One, how prevalent is lurking, and do health and software-support DLs differ? Two, how do lurking levels vary as the definition is broadened from zero posts in 12 weeks to 3 or fewer posts in 12 weeks? Three, is there a relationship between lurking and the size of the DL, and four, is there a relationship between lurking and traffic level?

When lurking is defined as no posts, the mean lurking level for all DLs is lower than the reported 90%. Health-support DLs have on average significantly fewer lurkers (46%) than software-support DLs (82%). Lurking varies widely ranging from 0 to 99%. The relationships between lurking, group size and traffic are also examined.


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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CITED BY  44

Collaborative Colleagues:
Blair Nonnecke: colleagues
Jenny Preece: colleagues