Real Clear Politics
 
Real Clear Science

 
 
 
 
July 30, 2014  
 
White Lies Make Social Networks  Stronger
By _Sylvia  Tippmann_ 
(http://www.realclearscience.com/authors/sylvia_tippmann/) 



“Lying is a bad thing – this is what mentors, parents and teachers tell 
us.  But there is no society without lies.”
 
So says theoretical physicist Rafael Barrio, and when he and his colleague  
Kimmo Kaski from the Aalto University School of Science in Finland thought 
about  this blatant discrepancy, the two computational scientists set out to 
simulate  the effects of lying in a virtual human population. Their 
results, published in  the _Proceedings of the  Royal Society B_ 
(http://dx.doi.org/10.1098/rspb.2014.1195) , show that lying is essential for 
the growth of a  
cohesive social network. 
The key to understanding the discrepancy is realising that all lies are not 
 equal. “White lies” or fibs, are generally accepted. Their intention is 
to  protect, benefit or help others, like reassuring a child on their efforts 
to  play violin to motivate future improvement. 
But some lies are selfish, when protecting oneself at the expense of 
another  person or even lying to hurt someone else intentionally. They are 
condemned in  most societies. In social psychology this behaviour is 
characterised 
as  “antisocial” lying while fibs are referred to as “prosocial”, as they 
help to  keep relations in good condition. 
Between two people, this classification is intuitive. But how does a whole  
population react to different types of lies? This is the question Barrio 
and his  team wanted to answer. They created a simple virtual scenario, which 
could then  be used to build computer models. 
In their scenario, 200 virtual individuals are connected by relationships 
of  different strengths and each is assigned a random opinion on a 
hypothetical  topic. Their one-on-one interactions make their levels of trust 
weaker 
or  stronger, depending on the type of lies these individuals use and that 
changes  the network of the society bit by bit. Some individuals were 
prosocial liars  whose actions have a higher probability of increasing trust, 
whereas some are  antisocial liars whose actions had a higher probability of 
decreasing trust. 
The researchers ran the model repeatedly for around 200,000 interactions  w
ithin the population, and recorded how the group structure evolves. “200,000 
 interactions is not much. In the real world, this is something that 
happens  between people in three to four days, the sort of thing when there is 
some bit  of news and everyone forms an opinion about it,” Barrio said. 
Not surprisingly, in a population where everyone is perfectly honest, trust 
 increases over time resulting in a well-connected group. But when Barrio  
decreased the level of honesty in the population by introducing either 
prosocial  or antisocial liars, he observed a different change. 
Antisocial deception led to fragmentation of the network, forming small and 
 tightly connected groups of honest individuals that are weakly connected 
by  dishonest agents. In an extreme case, when all agents in the model 
succumbed to  antisocial lying it destroyed the network structure and led to 
complete  isolation as a consequence. 
 
The structure of a virtual  society after interacting for a couple of days. 
_Gerardo  Iñiguez et al_ (http://arxiv.org/abs/1406.0673) , Author  provided
 
 
The effect of fibs, or prosocial lies, does not destroy the fabric of the  
virtual society. Instead, the network splits up into two large communities 
with  strong social links of like-minded honest agents within the community 
and weak  connections between the two big groups. These weak links are almost 
exclusively  established by dishonest agents, which suggests that prosocial 
lying might  actually enhance the cohesiveness in a society. 
In the model, the level of honesty and type of lying is fixed for each  
individual – but opinions may change. At the start of each simulation, when  
agents were randomly assigned opinions, some were undecided. Barrio and his 
team  observed that introducing more fibbing in the network reduced the number 
of  undecided agents and concluded prosocial lying actually help people 
make up  their mind. 
Alistair Sutcliffe, expert in systems engineering at the University of  
Manchester said, “The novelty in this study is the differentiation between  
social and antisocial lying. In reality the tolerance to fibbing depends on the 
 strength of the relationship.” 
But it doesn’t always take a computer model to work out whether lying is 
good  or bad. Charles Darwin understood the nature of lies almost 200 years 
ago. He  looked at his own son and concluded: “He is a liar but a good  chap.”

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