are already restructuring the ways in
which scholars form collaborations
and communicate their results.
used to be called the invisible college of
personal scholarly communications is
now a vast and highly visible, searchable, and influential infrastructure.
These new scholarly social networks,
the visible commons, ignite hot topics,
accelerate data sharing, and enable
rapid refinements to theories in ways
that were never before possible. For
example, in August 2010, when a researcher claimed to have proven one
of the most profound, challenging,
and elusive problems in all of mathematics and computer science (P=NP?),
blogs (such as http://rjlipton.word-
press.com), wikis, and other forms of
online communication conveyed active discussion about the proof—and
ultimately enabled a form of real-time
“peer review” that called into question
the researcher’s approach.
Scientists also have begun to use
social media to conduct new forms of
scientific research. NASA’s use of click-workers to measure Martian craters
( http://beamartian.jpl.nasa.gov) or the
Encyclopedia of Life’s ( http://eol.org)
integration of professional scientists
with trained citizen scientists and nature enthusiasts are examples of even
more potent methods. Scientists can
now engage with thousands of peers
as in the Gene Wiki (http://genwiki.eva.
mpg.de), with serious amateurs as in
star surveys ( http://galaxyzoo.org), or
with numerous paid workers through
services such as Mechanical Turk
( http://mturk.com). Such large-scale
collaborations could produce conflict
over credit for breakthroughs unless
new strategies for supporting trust
10, 15 Other ethical dilemmas come from the appropriateness
of existing Institutional Review Board
oversight processes or fairness of using low-paid Web-based labor in place
of traditional research assistants or experimental participants.
Call to action
These topics provoked lively discussions at two National Science Foundation (NSF)-funded workshops held in
the past year. The final report12 covers
descriptive, explanatory, prescriptive,
and predictive theories; opportunities
in health care/wellness and e-govern-
the next step will be
in the computing
sciences and in
ment; ethical issues for researchers;
design strategies for practitioners;
motivational challenges for community managers; research infrastructure
proposals; and innovative educational
reforms ( http://www.tmsp.umd.edu).
Some steps in expanding research
have already begun with the NSF’s
Social Computational Systems program ( http://www.nsf.gov/pubs/2010/
nsf10600/ nsf10600.htm) and the National Institutes of Health’s two programs on Social Network Analysis and
Health ( http://obssr.od.nih.gov/fund-ing_opportunities/foas/ faqs.aspx).
Researchers from many disciplines
can build on the ideas generated at
these workshops and summarized
here by working with funding agencies to restructure existing programs
so that social media research becomes
more widely supported. Evaluations
of civic social media projects could
make them more reliably successful
by developing validated design guidelines, effective community management strategies, advanced visual analytic and statistical tools, and broader
theories. Academics can spread this
new knowledge by introducing segments on social media into existing
courses, adding new courses, and
planning degree programs for professionals and researchers.
Adventurous researchers are al-
ready using social media to improve or
speed their research, but the next step
will be paradigm-shifting methods for
conducting scholarly research in the
computing sciences and in every dis-
cipline. Faster paths to curing cancer,
tracking climate change, mapping
species distribution, and much more
seem within reach. However, there is
also a risk that social media researchers
will soon confront ethical challenges as
serious as those that the nuclear physi-
cists faced in the 1950s. This time the
concerns will be about inequities in
Internet access, violations of privacy,
vulnerability to attacks, as well as tech-
nical failures and social chaos during
crises. We believe the computing sci-
ences community can rise to these chal-
lenges and find effective solutions.
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Everything We Do. Dutton, ny, 2010.
2. easley, D. and Kleinberg, J. Networks, Crowds, and
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Cambridge university Press, ny, 2010.
3. golbeck, J. Weaving a web of trust. Science, 321, 5896
4. hansen, D., shneiderman, b., and smith, M.a.
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12. Pirolli, P., Preece, J., and shneiderman, b., eds.,
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Framework: Motivating technology-mediated social
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Science 51, 6 (June 2005), 851–868.
Ben Shneiderman ( firstname.lastname@example.org) is a professor in the
Department of Computer science, the founding director
of the human-Computer interaction laboratory, and a
member of the institute for advanced Computer studies
at the university of Maryland at College Park.
Jennifer Preece ( email@example.com) is a professor and
dean of the information school at the university of
Maryland at College Park.
Peter Pirolli ( firstname.lastname@example.org) is a research fellow in
the augmented social Cognition area at the Palo alto
research Center (ParC).
We appreciate national science Foundation support
(iis-0956571) to conduct the two workshops and all
the participants in those workshops. We appreciate the
comments we received from the reviewers and James
Copyright held by author.