lutionary patterns of activity within homogeneous or heterogeneous small,
medium, and large organizations
could be studied with network analysis
tools to identify highly productive individuals or groups.
5, 8 Understanding
the dynamics of collective action, governance, and leadership in networked
organizations can present grand scientific challenges that are worthy of
Nobel Prize recognition, such as bestowed on Elinor Ostrom.
early successes such as Wikipedia and
health discussion groups generate
the impression that success in using
social media is inevitable, but the reality is that failure is the norm and even
successful projects have problems.
For Wikipedia, only one out of every
1,000 readers registers to make contributions—and even fewer participate
in durable collaborations. Higher
rates of participation are needed for
smaller projects to succeed.
One model of how participation
evolves is the Reader-to-Leader Framework (see Figure 1), which also offers
usability and sociability design guidelines.
13 This framework describes how
some of the large numbers of readers
mature into contributors who offer
user-generated content such as videos, photos, reviews, and ratings. A
smaller segment becomes intensely
involved in collaborative groups who
discuss substantive changes and expansions of content. Finally, a small
group of leaders emerge to set policies, deal with attacks, resolve disputes, and mentor newcomers. A major research effort could validate and
refine such frameworks, providing
not every computing
scientist will be
interested in studying
social media, but
social media research
can have a profound
impact on every
deeper insights into the nature of human motivation in different contexts.
The emerging science of online motivation draws on sociological studies
and political science theories, as well
as on statistical methods, agent-based
simulations, linguistic sentiment analysis, and network analysis/visualiza-tion.
4 For example, studying trust, in its
many forms, would lead to improved
designs that facilitate collaboration so
that participants can rapidly resolve
their differences and act effectively
when needed, as some environmental
groups did following the Gulf oil spill.
Another research topic is the grow-
ing availability of big social data,
presents significant challenges to algo-
rithm designers and mathematicians
possibly requiring innovative chip de-
signs to accelerate the necessary com-
putations. Just as graphical processing
units (GPUs) have enabled rapid 3D ex-
ploration, social processing units (SPUs)
may be needed to enable scalable so-
cial network analysis for computations
such as eigenvector centrality, com-
munity clustering, and comprehen-
sible layouts. While Moore’s Law has
signaled the steady progress of hard-
ware technologies in petaflops and
gigahertz, new laws could describe the
growth of massive projects by measur-
ing peta-contribs and giga-collabs.
figure 1. the Reader-to-Leader framework suggests the evolutionary path for participants in social media communities. some users may
move smoothly through the four phases, while others may take different paths as indicated by the arrows in the figure.