Biomedical Engineering Reference
In-Depth Information
perhaps counterintuitive: “Make it easy” would seem to encourage a more
democratic, representative outcome. But the data sets behind Figure 6.6 are
so large that we must take very seriously the possibility that “make it hard and
specifi c” is the better way to assure a broader source of input.
Of equal concern are the very large scale observations of fi ve - star voting
at Amazon [20], namely that it is biased, compressed (with an average of 4.4
out of fi ve stars), and prone to follower behavior that drives to extreme opin-
ions rather than balance. Consistent with the observation of Figure 6.6, the
authors recommend making the online book review process more diffi cult,
rather than less, to achieve better quality and balance.
6.8
CONCLUSIONS
Multiple large data sets from diverse private and public sources show that
contributions to large-scale voluntary collaboration campaigns (including sci-
entifi c challenges) generally follow a power law and with an exponent consid-
erably higher (
α
=
2.7
±
0.3) than “ easier ” tasks (Twitter, Digg, fi ve - star rating;
α
2-2.2). The consequence is that these campaigns depend for a majority of
their content on a “long tail” of people who contribute only a couple of ideas
each. Because power laws are scale free, this generalization applies to small
as well as global-scale campaigns. The phenomenon may benefi t from, but does
not depend on, social networks because blinded “drop box” challenges have
the same signature. Thus, rather than speak of “communities,” we would be
more accurate to refer to “personal responses to a particular challenge.” To
encourage participation, we should respect our contributors as individuals,
recognize quality over quantity, and remember the strong motivation of con-
tributing to real work that makes a difference. Large-scale collaborative evalu-
ation of options is more problematic, since the data for popular techniques
like promote-demote and fi ve-star voting reveal a potential for considerable
bias and dominance of minority opinions.
ACKNOWLEDGMENTS
The author, recently retired as Senior Research Fellow at Pfi zer, wishes to thank Steve
Street for his support and courage to embrace change as well as Tim Woods at
Imaginatik, Doug Phillips at Pfi zer, and Anne Rogers and Kurt Detloff at Cargill for
sharing anonymized data.
REFERENCES
1. Summary of NDA Approvals & Receipts, 1938 to the present. Available: http://
www.fda.gov/AboutFDA/WhatWeDo/History/ProductRegulation/Summaryof
NDAApprovalsReceipts1938tothepresent/default.htm . Accessed July 5. 2010 .
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