December 2020, ScientificAmerican.com 57SOURCE: “LIMITED INDIVIDUAL ATTENTION AND ONLINE VIRALITY OF LOW-QUALITY INFORMATION,” BY XIAOYAN QIU ET AL., IN
NATURE HUMAN BEHAVIOUR,VOL. 1, JUNE 2017comprehend the cognitive vulnerabilities of social
media users. Insights from psychological studies on
the evolution of information conducted at Warwick
inform the computer models developed at Indiana,
and vice versa. We are also developing analytical and
machine-learning aids to fight social media manipu-
lation. Some of these tools are already being used by
journalists, civil-society organizations and individu-
als to detect inauthentic actors, map the spread of
false narratives and foster news literacy.INFORMATION OVERLOAD
the glut of informAtion has generated intense compe-
tition for people’s attention. As Nobel Prize–winning
economist and psychologist Herbert A. Simon noted,
“What information consumes is rather obvious: it con-
sumes the attention of its recipients.” One of the first
consequences of the so-called attention economy is
the loss of high-quality information. The OSoMe team
demonstrated this result with a set of simple simula-
tions. It represented users of social media such as
Andy, called agents, as nodes in a network of online
acquaintances. At each time step in the simulation, an
agent may either create a meme or reshare one that
he or she sees in a news feed. To mimic limited atten-
tion, agents are allowed to view only a certain num-
ber of items near the top of their news feeds.
Running this simulation over many time steps, Lil-
ian Weng of OSoMe found that as agents’ attentionbecame increasingly limited, the propagation of memes
came to reflect the power-law distribution of actual
social media: the probability that a meme would be
shared a given number of times was roughly an inverse
power of that number. For example, the likelihood of
a meme being shared three times was approximately
nine times less than that of its being shared once.
This winner-take-all popularity pattern of memes,
in which most are barely noticed while a few spread
widely, could not be explained by some of them being
more catchy or somehow more valuable: the memes
in this simulated world had no intrinsic quality.
Virality resulted purely from the statistical conse-
quences of information proliferation in a social net-
work of agents with limited attention. Even when
agents preferentially shared memes of higher quali-
ty, re searcher Xiaoyan Qiu, then at OSoMe, observed
little improvement in the overall quality of those
shared the most. Our models revealed that even
when we want to see and share high-quality infor-
mation, our inability to view everything in our news
feeds inevitably leads us to share things that are part-
ly or completely untrue.
Cognitive biases greatly worsen the problem. In a
set of groundbreaking studies in 1932, psychologist
Frederic Bartlett told volunteers a Native American
legend about a young man who hears war cries and,
pursuing them, enters a dreamlike battle that even-
tually leads to his real death. Bartlett asked the vol-Each circle
represents a social
media accountFew Number of Different Memes in Play Many
Information load is low, and quality
of shared information is highInformation load is high, and quality
of shared information is low
Different colors represent
different memes
Meme A
Meme B
Meme CCircle size
indicates quality
of last meme sharedLowHighLines represent
connections
between accountsInformation Overload
Our social media newsfeeds are often so full that many of us can
view only the top few items, from which we choose to reshare or
re tweet. Researchers at the Observatory on Social Media (OSoMe)
at Indiana University Bloomington simulated this limited capacity
to pay attention. Each node in the model network represents auser, linked by lines to friends or followers who receive the items
they share or reshare. Investigators found that as the number of
memes in the network rises ( toward the right ), the quality of those
that propagate widely falls (circles become smaller). So information
overload can alone explain why fake news can become viral.