Charting the Climb

August 9, 2012
Posted by Jay Livingston

Isabella was the second most popular name for baby girls last year.  She had been number one for two years but was edged out by Sohpia.  Twenty-five years ago Isabella was not in the top thousand. 

How does popularity happen?  Gabriel Rossman’s new book Climbing the Charts: What Radio Airplay Tells Us about the Diffusion of Innovation offers two models.*   People’s decisions – what to name the baby, what songs to put on your station’s playlist (if your job is station programmer), what movie to go see, what style of pants to buy –  can be affected by others in the same position.  Popularity can spread seemingly on its own, affected only by the consumers themselves communicating with one another person-to-person by word of mouth.  But our decisions can also be influenced by people outside those consumer networks – the corporations or people who produce and promote the stuff they want us to pay attention to.

These outside “exogenous” forces tend to exert themselves suddenly, as when a movie studio releases its big movie on a specified date, often after a big advertising campaign.  The film does huge business in its opening week or two but adds much smaller amounts to its total box office receipts in the following weeks.   The graph of this kind of popularity is a concave curve.  Here, for example, is the first  “Twilight” movie.



Most movies are like that, but not all.  A few build their popularity by word of mouth.  The studio may do some advertising, but only after the film shows signs of having legs (“The surprise hit of the year!”).  The flow of information about the film is mostly from viewer to viewer, not from the outside. 

This diffusion path is “endogenous”; it branches out among the people who are making the choices.  The rise in popularity starts slowly – person #1 tells a few friends, then each of those people tells a few friends.  As a proportion of the entire population, each person has a relatively small number of friends.  But at some point, the growth can accelerate rapidly.  Suppose each person has five friends.  At the first stage, only six people are involved (1 + 5); stage two adds another 25, and stage three another 125, and so on.  The movie “catches on.” 

The endogenous process is like contagion, which is why the term “viral” is so appropriate for what can happen on the Internet with videos or viruses.   The graph of endogenous popularity growth has a different shape, an S-curve, like this one for “My Big Fat Greek Wedding.”



By looking at the shape of a curve, tracing how rapidly an idea or behavior spreads, you can make a much better guess as to whether you’re seeing exogenous or endogenous forces.  (I’ve thought that the title of Gabriel’s book might equally be Charting the Climb: What Graphs of Diffusion Tell Us About Who’s Picking the Hits.)

But what about names, names like Isabella?  With consumer items  – movies, songs, clothing, etc. – the manufacturers and sellers, for reasons of self-interest, try hard to exert their exogenous influence on our decisions.  But nobody makes money from baby names.  Still, those names can be subject to exogenous effects, though the outside influence is usually unintentional and brings no economic benefit.  For example, from 1931 to 1933, the first name Roosevelt jumped more than 100 places in rank. (That was in an era when the popularity of names was more stable. Now, names are more volatile. Nowadays, 50 or more boys names may jump 100 places or more in a single year.)

When the Census Bureau announced that the top names for 2011 were Jacob and Isabella, some people (including, I think, Gabriel) suspected the influence of an exogenous factor – “Twilight.”  

 I’ve made the same assumption in saying (here) that the popularity of Madison as a girl’s name – almost unknown till the mid-1980s but in the top ten for the last 15 years – has a similar cause: the movie “Splash” (an idea first suggested to me by my brother).  I speculated that the teenage girls who saw the film in 1985 remembered Madison a few years later when they started having babies. 

Are these estimates of movie influence correct? We can make a better guess at the impact of the movies (and, in the case of Twilight, books) by looking at the shape of the graphs for the names.



Isabella was on the rise well before Twilight, and the gradual slope of the curve certainly suggests an endogenous contagion.  It’s possible that Isabella’s popularity was about to level off  but then got a boost in 2005 with the first book. And it’s possible the same thing happened in 2008 with the first movie. I doubt it, but there is no way to tell.

The curve for Madison seems a bit steeper, and it does begin just after “Splash,” which opened in 1984.  Because of the scale of the graph, it’s hard to see the proportionately large changes in the early years.  There were zero Madisons in 1983, fewer than 50 the next year, but nearly 300 in 1985.  And more than double that the next year.  Still, the curve is not concave.  So it seems that while an exogenous force was responsible for Madison first emerging from the depths, her popularity then followed the endogenous pattern.  More and more people heard the name and thought it was cool.  Even so, her rise is slightly steeper than Isabella’s, as you can see in this graph with Madison moved by six years so as to match up with Isabella.



Maybe the droplets of “Splash” were touching new parents even years after the movie had left the theaters.

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* Gabriel posted a short version about these processes when he pinch hit for Megan McCardle at the Atlantic (here).

“What Do You Know?” (Information Asymmetry)

August 6, 2012
Posted by Jay Livingston
(Cross-posted at Sociological Images)


I bought a used book on Amazon, and when I opened it, I felt as though I were an unintentional eavesdropper.  I had stumbled into a triangle of information asymmetry. 

Examples of asymmetry and other information distributions usually come from games or economics.  There’s “perfect information” (chess) and “imperfect information” (card games).  The best known example of “information asymmetry” is still Akerlof’s “The Market for Lemons” (cars, not fruit). 

In all these examples, the information is about objects.  But in everyday life, information is often about people, not chess pieces or cards or Camaros.  Perfect information is rare.  I know more about myself than you do, and vice versa.  Usually.  But what if you know something about me that I don’t know? What if you have seen my hole cards, and I haven’t?* 

Last week’s  “This American Life” started with a story about that unusual arrangement.  But the information wasn’t about a man’s cards, it was about his life (or more precisely, his wife).

The man discovers that his wife is seeing another man.  Even though the couple were in the process of separating, he is devastated.  He turns, as Ira Glass says, “to someone he knows will be on his side, will help him make sense of this, tell him what to do – his lawyer.”  For a tear-filled hour, he talks to his lawyer.  Only later does he discover that the lawyer is the man his wife has been having the affair with.

The information – who knows what about who – badly lacks symmetry.  The man, talking to his lawyer, lacks a crucial piece of information, information that the lawyer could provide.  Instead, the  lawyer pretends to be ignorant and lets the man go on for an hour talking and weeping.

(This three-person asymmetric structure, save for the lawyer-client angle, is identical to that of the Salinger story, “Pretty Mouth and Green My Eyes.”)

My own used-book story is a less dramatic version of this same asymmetry.

The book was listed as “used – like new, signed by the author.”  I considered getting a clean copy for the same price from a different seller but went with this one. It arrived – gift wrapped, for some reason – and indeed, the book was like new.  Unread.  And it was not just signed.  There was a personal message: “For Gerry,** since you’re so much a part of this.” 

I was sure I knew who Gerry was – the name (the actual name, not this nom-de-blog) is not a common one.  I remembered that Gerry, now a professor at a major university, was a student of the author’s long ago. 

They live in the same area, and I assume they have a closer relationship to one another than I have to either of them.  (I know the author slightly, Gerry not at all.)  After all, there’s that inscription in the book.  But I now have a piece of information that says something about their relationship, a fact known to only one of them – Gerry.   And neither of them knows that I am now in on this bit of information. 

I could let the author in on this information. “Hey, did you know that copy of your book you inscribed so nicely?  Gerry didn’t even read it and then went and sold it to some resale shop.”  But of course I won’t.  Still, this little incident gives me some sympathy with that lawyer.

The “This American Life” story made him out as the bad guy, and in fact, he was charged with professional misconduct.  At the disciplinary hearing, when asked why he didn’t just tell his client to find another lawyer, he says, “Well, to be honest, it was very awkward. It was one of those things I just wasn't sure how to bring up or when to bring up.” 

Neither am I.  And I’ll never have to.

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* A symmetrical version of this self-ignorance is the basis for a card game that I know as One-Card Schmuck but which I can find on the Internet only as Indian Poker or Blind Man’s Bluff (here, for instance).  The Indian Poker is definitely un-PC, Blind Man’s Bluff more accurate.  But One-Card Schmuck captures the essence of the game.

** Not the real name, and deliberately gender-ambiguous.

Plagiarism? Bah, Humbug

August 2, 2012
Posted by Jay Livingston

The section on plagiarism in my syllabus is fairly short.  It lists the possible penalties, and it has a link to the University page on plagiarism – what it is and how to avoid it.  But I’ve seen some syllabi whose plagiarism sections seemed to me like a big production.  I was wrong.  If you want to see a big production, try this.  (And don’t forget to click on the CC for subtitles.)




HT: Andrew Gelman

Beyond the Gee Whiz Graph – the OMG Graph

August 1, 2012
Posted by Jay Livingston

How to make a 13% increase (4.6 percentage points) look like a quintupling.

I’ve blogged before about “gee-whiz graphs” (here and here ). And I’ve blogged about the inventive graphing techniques of the folks at Fox (here).  But this example may be in a class by itself.
 


In case the numbers are not clear:  Now = 35%, Jan. 1. 2013 = 39.6%.  The heights of the bars make a 13% increase appear as a 400% increase.

HT: I’m not sure who posted this first.  I got it thanks to Sangeeta Parashar.