Twitter Terrorists: False information + positive feedbacks = real panic

Another example of how false information, amplified through positive feedbacks, can lead to real panic: in Veracruz Mexico two people posted messages on twitter reporting kidnappings at a local school. The messages spread rapidly through social media leading frightened parents to rush to try and save their children. The panic caused dozens of car accidents and jammed the city's emergency phone lines.

Amnesty International was quoted saying, "The lack of safety creates an atmosphere of mistrust in which rumours that circulate on social networks are part of people's efforts to protect themselves, since there is very little trustworthy information." As with many "tipping point" phenomenon, before the spark that set off the visible cascade, there was most likely a "contextual tipping point" that made the resulting contagion possible. Governments or managers have to realize that the only way to reliably prevent these cascades is by changing the context, not by stamping out all of the sparks.

The S&P credit downgrade, turmoil in the markets, and the 1973 toilet paper shortage

On Friday, August 5, Standard & Poor's downgraded the credit rating of the U.S. long-term debt to AA+.  On Monday, the first day the markets opened since the downgrade, the Dow Jones Industrial average dropped 5.6 percent and the S&P 500 fell 6.7 percent — the biggest single day drops since the crisis in 2008.  A lot of people might be confused about this turmoil in the markets, since US debt is still considered one of the safest investments there is.  Jay Forrester, founder of the field of System Dynamics, calls puzzles like this the "counterintuitive behavior of social systems."

Undoubtedly, the world economy is incredibly complex, and no individual or organization has a complete picture of how it works or where it's headed.  Through pricing, the market is supposed to aggregate all of the pieces of partial information that we each hold and then converge to the "truth" — that is prices should reflect true underlying value.  In some situations this can actually work.  Prediction markets have been shown to be valuable tools for businesses to harvest the "wisdom of the crowds" and assess the probabilities that future events occur.  But, this mechanism works best when individuals place their trades independently based on their own private information. In the real world, market dynamics are fundamentally social dynamics and as such they are subject to cascades of panic and the accumulation of overconfidence (what Alan Greenspan famously referred to as "irrational exuberance" (see also Robert Shiller)).


The current panic illustrates how even when there is no fundamental basis for a panic, social dynamics can amplify the signal of a panic to the point where an actual crisis ensues.  The gas shortages of 1979 are a classic example of this phenomenon.  The Iranian revolution sharply cut oil imports to the US from Iran.  Nervous consumers rushed to top off their tanks and even to hoard gasoline at home.  This drained the supply of gasoline at filling stations leading to an actual gasoline shortage.  Word-of-mouth and media coverage reinforced consumer fears of shortages, leading to even more topping off and hoarding, as well as government policies such as odd/even day purchase rules that actually further incentivized consumers to top off frequently and store gasoline at home.  Surprisingly, despite the very real shortage of gasoline at filling stations, US oil imports for the year actually increased in 1979 compared 1978.  The crisis was caused by social dynamics, not an actual drop in supply. (See Sterman, Business Dynamics p. 212).

A similar but more comical crisis occurred in 1973 when Johnny Carson made a joke saying, "You know what’s disappearing from the supermarket shelves?  Toilet paper.  There’s an acute shortage of toilet paper in the United States."  Consumers rushed out to stock up on toilet paper, leading to a real toilet paper shortage in the US that lasted several days.  Even though Carson tried to correct the joke a few days later, by that time toilet paper was in fact in short supply because people were hoarding it at home.

Another Social Media Disaster: The Milk "Everything I Do is Wrong" campaign

The New York Times chronicles another example of an online ad campaign gone bad.  This time the California Milk Processor Board ran a campaign at (since replaced with touting the abilities of milk to help reduce PMS symptoms that clearly made light of women from a stereotyped males perspective.  As we well know by now, in the age of social media, a misstep like this can quickly turn into a disaster.

The Christakis and Fowler Social Networks Influence Brouhaha

Recently there has been a spirited conversation kicked off by the publication of an article, "The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis," by Russell Lyons regarding the well-publicized work of Nicholas Christakis and James Fowler on social contagion of obesity, smoking, happiness, and divorce.  The discussion has been primarily confined to the specialized circle of social network scholars, but now that conversation has spilled out into the public arena in the form of an article by Dave Johns in Slate (Dave Johns has written about the Christakis-Fowler work in Slate before).  Christakis and Fowler's work has received a huge amount of attention, appearing on the cover of the New York Times magazine, on the Colbert Report TV program, and a ton of other places (see James's website for more links).  Many others have made detailed comments on Lyon's article and on the original Christakis-Fowler papers.  I wish to address some of the related issues raised in Slate about scientists in the media

The article seems to criticize Christakis and Fowler for their media appearances, as though this publicity is inappropriate for scientists who should be diligently but silently working in the background, leaving it up to policy makers and the media to make public commentary and recommendations.  I think this criticism is not only wrong, but dangerous.  Many if not most researchers do work silently in the background, shunning the spotlight and scrutiny of the media, not out of shyness or fear of embarrassment, but because of a pervasive misunderstanding of scientific uncertainty.  Hard science is simply much softer than many people realize.

ALL scientific conclusions — from physics to sociology come with uncertainty (this does not apply to mathematics, which is actually not a science).  A "scientific truth" is actually something that we're only pretty sure is true.  But we'll never be definitely 100% sure, that's just how science works.  When one scientist says to another, we have observed that X causes Y, it is understood that what is meant is, the probability that the observed relationship between X and Y is due to chance is very small.  But, statements like that don't make for good news stories.  Not only are they uninteresting, but for most people they're unintelligible (which is not to say that the public is stupid — the concepts of uncertainty and statistical significance are extremely subtle and often misunderstood even by well-trained scientists).  So, many scientists avoid the media because we're asked to make definitive statements where no definitive statements are possible, or we make statements that include uncertainty that are ignored or misunderstood.

But we need scientists in the media.  Only a fraction of Americans believe the planet is warming and 40% of Americans believe in creationism.  Scientists in the media can help correct these misperceptions and guide public policy.  And, maybe even more importantly, scientists in the media can make science sexy.  We already live in a world where science and politics are often at odds, and in which scientists that avoid the media are often overruled by politicians that seek it out.  Scientists are already wary of making public statements that implicitly contain uncertainty for fear of them being interpreted as definitive. Christakis and Fowler have done us a great service by taking the risk of making statements and recommendations in the public arena based on the best of their knowledge, by raising public awareness of the science of networks, and by making science fun, interesting, and relevant.

Social Networks in the Classroom

Today's New York Times has an article on an educational software start-up that "has a social-networking twist."  The company, Piazza, provides a course page where students can ask and answer questions with moderation from the instructor.  I'm not sure what the "social networking" component of this site is.  From the Times article, it sounds simply like a message board with a few bells and whistles.  A quick search for the company's website left me empty handed, so we can only speculate that there is actually something more here.

In passing, the article raised another interesting point though: "As in the case of Facebook, the wildly popular social network that sprang from a Harvard dorm room, the close-knit nature of college campuses has helped accelerate the adoption of Piazza."  The idea that close-knit communities lead to increased technology adoption is something that I prove in my recent paper, "Friendship-based Games."  The idea of closely knit communities is captured by the clustering coefficient of a network.  This metric measures the probability that two individuals that share a mutual friend are friends with one another.  In the paper, I show using a game theoretic model that new (beneficial) technologies have an easier time breaking into a market in networks with high clustering.  The basic idea is that small communities of users can adopt the new technology and interact mainly with one another, protecting themselves from the incumbent.  This may be one of the reason that college campuses, which probably exhibit higher clustering than many other social networks, prove to be such fertile ground for the adoption of new innovations.

Nicholas Christakis at WIDS@LIDS

Today and tomorrow I’m at the Interdisciplinary Workshop on Information and Decision in Social Networks at the MIT Laboratory for Information and Decision Systems (WIDS@LIDS).  Nicholas Christakis gave a thought provoking talk this morning drawing on a lot of material from his book, Connected, written with James Fowler.  One of the first ideas he raised is that humans are unique in having a social pressure on our evolution.  Humans  and other species also face environmental and other species evolutionary pressures.  But, he argued that humans are unique in this social pressure because we live in close proximity and other human groups are one of the biggest threats that  we face.  He went on to say that possibly this unique social pressure is responsible for humans evolving intelligence, because in order to navigate the complexities of social interactions, we need substantial intelligence.  I’m not sure that I buy this argument though.  What about ants, bees, wolf packs, ... ?  All of these species work in groups, cooperate, and face competitive pressure from other groups, but none of them have evolved intelligence on a human scale.

Christakis ended his talk asking about why certain ideas are “sticky.”  I think this is a super interesting and super difficult question.  I’ve been talking with Adam Berinsky in the Political Science Department at MIT about this question in relation to political rumors.  Why does the rumor that Obama was born in another country stick around, but other rumors die out?  Christakis suggested that this might somehow be a tractable question, but I think it is much more subtle.  First of all, there are no natural metrics for judging ideas.  Second of all, we can’t just look at which ideas have actually taken off and which haven’t, because so many other chance factors come into play.  Because of the big positive feedbacks involved in the spread of ideas, this process is highly susceptible to chance tipping (see the work by Salganik, Dodds, and Watts).  It’s very east to fall into the trap that Duncan Watts sums up in the title of his recent book, Everything is Obvious Once You Know the Answer.  Once an idea does “go viral,” like the Birther rumor, it is tempting to make up a narrative that says, well of course that rumor spread because it has attributes x, y, and z.  But, if the rumor had died we could just as easily construct a different narrative explaining its failure.  Paul Lazarsfeld’s paper on The American Soldier gives a fantastic example of how we can trick ourselves into believing this kind of after the fact rationalization.

"I mourn the loss of thousands of precious lives ... "

There is a great story on the Atlantic’s website about a fake quotation that exploded on Facebook and Twitter after Osama Bin Laden’s death.  The quote, wrongly attributed to Martin Luther King Jr. is:

“I mourn the loss of thousands of precious lives, but I will not rejoice in the death of one, not even an enemy.”

The author of the article, Megan McArdle, traces the origins of the wrongly attributed quote to a facebook post from a 24 year old Penn State graduate student (check out the article for the fascinating story).  This brings up some interesting issues about rumors and social media.  An open question regarding information and the web, is whether technologies like social media and the Internet in general increase or decrease the prevalence of false information.  On the one hand, the “wisdom of the crowd” might be able to pick out the truth from falsehoods.  True statements will be repeated and spread, while false statements will be recognized by a great enough number of people to squelch them.  On the other hand, we know that systems like this with strong positive feedbacks can converge to suboptimal solutions.  If you think of retweeting some piece of information as like casting a vote that it is true, we might expect information cascades of the sort described theoretically by Bikhchandani et al..  In this case, two things seem to have happened.  Initially, there was a sort of information cascade that led to the spread of the quote.  Then it wasn’t the wisdom of the crowds that led to the squelching of the rumor, but the efforts of knowledgable individuals tracing the quotation back to the initial post.  What the Internet provided was a way to uncover the roots of the false information for those willing to take the time to look.

Social Dynamics of the Bin Laden Death Celebration

Many people, including myself, have been a little disturbed by the wild celebrations of Osama bin Laden’s death.  An article in the New York Times quotes a number of psychologists that explain the partying as natural cathartic “pure existential release.”  It’s not until the last two paragraphs of the article that they hit on what I think was the real driving force behind the “chanting and frat-party revelry”: crowd dynamics.  The article says, “in a crowd of like-minded people, the most intense drives for justice become the norm: People who may have felt a mix of emotions in response to the news can be swept up in the general revelry.”

The dynamic is similar to that detailed by Cass Sunstein in his book Going to Extremes (I’m currently writing a paper that develops formal models to explain the going to extremes dynamic)Sunstein describes a pile of social psychology research demonstrating that when like minded individuals discuss their opinions, they become more extreme, rather than converging to the mean.  A prime example is risk taking among teenagers, a bunch of kids that would never try driving their car 150 miles an hour or shotgunning cases of beer on their own, will turn into drunken race car drivers in a crowd of their peers.  I imagine the dynamic was much the same around the Georgetown bars last Sunday night.  Riots can erupt the same way.  Most people wouldn’t think of throwing bricks threw store windows or setting cop cars on fire, but in the midst of a rioting crowd our behavior can be much different.

Homophily and Information Spread

This article in Wired covers new research on networks and information by Sinan Aral (Northwestern B.A. in Political Science, MIT Sloan PhD, now at NYU Stern) and Marshall Van Alstyne.  The article describes research on the email communications of members of an executive recruiting firm, and says, “those who relied on a tight cluster of homophilic contacts received more novel information per unit of time.”  The article is confusing though because it mixes several distinct network concepts: homophily, strong ties, clustering, and “band width.”  Homophily is the tendency for people to be connected to other people that are similar to them; birds of a feather flock together. In his seminal paper, “The Strength of Weak Ties,” Mark Granovetter defined the strength of a tie as “a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding), and the reciprocal services which characterize the tie”.  Clustering measures the tendency of our friends to be friends with each other.  And bandwidth is a less standard term in the social networks literature that captures the total amount of information that flows through a given tie per unit time (and thus is about the same thing as strength of a tie).

After reading the Wired piece, I’m left wondering if it is

  1. strong or “high bandwidth” ties through which we communicate a lot of total information,
  2. homophilic ties with people that are similar to us,
  3. ties with people that are members of a tightly knit cluster of friends, or
  4. all of the above

that provide us with the most novelty in our information diet.

A look at the original research article makes it more clear why the Wired article was so confusing.  The actual argument has a lot of moving pieces to it.  The first argument is that structurally diverse networks tend to have lower bandwidth ties.  Here structurally diverse appears to mean not highly clustered.  So, you talk more to the people in your personal clique than to people outside of your tightly knit group.  The second piece relates structural diversity to information diversity.  They find that the more structurally diverse the network, the more diverse the information that flows through it.  So far, this seems to line up with the standard Granovetter weak ties story.  The third relationship is that increasing bandwidth also increases information diversity, and more importantly, increasing bandwidth increases the total volume of new (non-redundant) information that an individual receives.  The idea here is that if you get tons of information from someone, some of it is going to be new.

Finally, since both structural diversity and bandwidth increase information diversity, but structural diversity decreases with increased bandwidth, they set up a head to head battle to see whether the information diversity benefits of increasing bandwidth outweigh the costs of reducing structural diversity.  They have three main findings on this front that characterize when bandwidth is beneficial:

  • “All else equal, we expect that the greater the information overlap among alters, the less valuable structural diversity will be in providing access to novel information.”
  • “All else equal, the broader the topic space, the more valuable channel bandwidth will be in providing access to novel information.”
  • “All else equal, ... the higher the refresh rate, the more valuable channel bandwidth will be in providing access to novel information.”