CONSISTENT PATTERNS IN LARGE - SCALE COLLABORATION - Collaborative Computational Technologies for Biomedical Research - page 106

from power law at the bottom right. When large voluntary individual cam-
paigns alone are considered, the tail extends farther [9, Fig. 5a], with the con-
sequence that fully half of the total entries (and therefore value) come from
people who only ever contribute once [9, Fig. 8].

6.5 COMMUNITIES?

We have seen that voluntary, large-scale, collaborative challenges on scientifi c
topics are feasible, sustainable, and technically well understood and that a
great deal of the value derived comes from the occasional contributors. But
are these really “communities,” or is that word becoming overworked, in the
same way that calling a stranger who accesses your blog or photos a “friend”
does not make them one. It is more than a semantic quibble if our beliefs affect
our strategies for attracting new participants or rewarding and recognizing
past contributors.
We have one relevant data set, but it is objective and large scale. For years
Pfi zer, like many companies, has had a link on its public website, saying in
effect, “send us your ideas to improve our offerings.” Figure 6.5 shows the
familiar rank-frequency plot for several years of this activity; again, it is an
excellent power law. What this data set has in common with the others is that
it is from a large-scale voluntary process, seeking new ideas and concepts for
business purposes. Where it differs is that for intellectual property and legal
reasons the process has been implemented as a “drop box,” in which contribu-

Figure 6.5 Rank-frequency plot for unsolicited open website suggestions. The line
has exponent α = 3 .