“When times are mysterious
Serious numbers will speak to us always.
That is why a man with numbers
Can put your mind at ease.
We’ve got numbers by the trillions
Here and overseas.”
—Paul Simon, “When Numbers
Get Serious,” 1983
Increasingly in the 21st century,
our daily lives leave behind a
detailed digital record: our shifting
thoughts and opinions shared on
Twitter, our social relationships,
our purchasing habits, our information
seeking, our photos and
videos—even the movements of
our bodies and cars. Naturally, for
those interested in human behavior,
this bounty of personal data
is irresistible. Decision makers of
all kinds, from company executives
to government agencies to
researchers and scientists, would
like to base their decisions and
actions on this data. In response,
a new discipline of big data analytics
is forming. Fundamentally, big
data analytics is a workflow that
distills terabytes of low-value
data (e.g., every tweet) down to,
in some cases, a single bit of
high-value data (Should Company
X acquire Company Y? Can we
reject the null hypothesis?). The
goal is to see the big picture from
the minutia of our digital lives.
It is no surprise today that big
data is useful for HCI researchers
and user interface design. As one
example, A/B testing is a standard
practice in the usability community
to help determine relative
differences in user performance
using different interfaces. For
many years, we have used strict
laboratory conditions to evaluate
interfaces, but more recently we
have seen the ability to implement
those tests quickly and on a large
population by running controlled