program or find a video that helps kids solve tough algebra problems, they
can easily hit the Share button or copy and paste the link into an e-mail.
Most major news or entertainment websites take the extra step of
documenting what has been passed along most frequently. Listing which
articles, videos, and other content have been most
viewed or shared over the
past day, week, or month.
People often use these lists as shortcuts. There is way too much content
available to sift through it all—hundreds of millions of websites and blogs,
billions of videos. For news alone, dozens of highly reputable outlets
continuously produce new articles.
Few people have time to seek out the best content in this ocean of
information. So they start by checking out what others have shared.
As a result, most-shared lists have a powerful ability to shape public
discourse. If an article about financial reform happens to make the list,
while one about environmental reform barely falls short, that initially small
difference in interest can quickly become magnified. As more people see
and share the article about financial reform, citizens may become convinced
that financial reform deserves more governmental attention than
environmental reform, even if the financial issue is mild and the
environmental issue severe.
So why does some content make the Most E-Mailed list while other
content does not?
For something to go viral, lots of people have to pass along the same
piece of content at around the same time. You might have enjoyed Denise
Grady’s cough article, and maybe you shared it with a couple of friends.
But for the piece to make the Most E-Mailed list, a large number of people
had to make the same decision you did.
Is this just random? Or might there be some consistent patterns
underlying viral success?
SYSTEMATICALLY
ANALYZING THE MOST E-MAILED
LIST
The life of a Stanford graduate student is far from grand. My office, if you
could call it that, was a high-walled cubicle. It was tucked up in a
windowless attic of a 1960s-era building whose architectural style has often
been described as “brutalist.” A short, squat structure with concrete walls so
Luckily my colleague Katherine Milkman suggested a vastly improved
method. Rather than pull this information from the print newspaper by
hand, why not automate the process?
With the help of a computer programmer, we created a Web crawler. Like
a never tiring reader, the program automatically scanned
The New York
Times home page every fifteen minutes, recording what it saw. Not only the
text and title of each article, but also who wrote it and where it was featured
(posted on the main screen or hidden in a trail of links). It also recorded in
which section of the physical paper (health or business, for example) and on
what page the article appeared (such as the front page or the back of the
third section).
After six months we had a huge data set—every article published by
The
Dostları ilə paylaş: