May 13, 2011
|Google and other search engines are killing the ancient art of witty headline writing. Or are they?
Much has been tweeted about a blog post that appeared on the web site of the Atlantic the other day. In it, the writer lamented that online media, with their obsession for attracting traffic from search engines, are changing the way that headlines are written.
Google and other search engines categorize web pages based on their content, and give more relevance to what’s in the headline than to what is in regular text. So if you want people to find your page when they search for articles on Leonard Nimoy’s recent interest in cooking, you shouldn’t call it “Spice: The Final Frontier.” Instead, use something dry and descriptive, like “Leonard Nimoy Cooks,” the blogger wrote.
No more will we read witty puns or just cute expressions. As print media disappear, the future of an ancient art is at stake. Or is it?
Actually, I think that the whole thing is overblown. With a few tweaks to its design, a news site can give you the best of both worlds–you can keep your cute headlines while still getting Google to rank you just as highly as before.
First of all, the headline of your article isn’t even the most important component of your page, as far as search engines are concerned. Other pieces of information, such as the HTML title (the one that appears on the title bar of the browser window) or the URL are given more weight — although no one knows exactly by how much because search companies keep their ranking recipes as closely guarded secrets.
Second, you can design your web site to get around the headline problem. News media can pair a witty headline with a more descriptive subhead, and often do; to optimize your web search rankings the trick is to make the search engine think that your subhead is actually the headline. Fortunately, HTML allows you to do that because there is no connection whatsoever between what is tagged as a headline “under the hood” (in the HTML code that search engines crawl) and what looks like a headline to the reader.
To exemplify what I am saying, I made up a little web stand-alone, bare-bones page entitled “Insert Cute Pun Here: Why Google won’t kill witty headlines.”
That page has a headline that is completely uninformative and devoid of the keywords and key phrases that could make it easy for readers to find it through Google. But it also has a subhead that tells you what the story is about and is full of important keywords and key phrases. What you have to do is signal Google that the subhead is what it really should look at, not the headline, when ranking your page.
To do so, you have to set the “style sheet” for your web site and the way it presents pages appropriately. Style sheets are sets of prescriptions for how your web site will look and feel, and they are customarily saved as a separate page, so that they can be shared by all pages on a site. For simplicity, in my sample page I have included the style sheet in the page itself. In it, I have set the size, fonts, etc. for displaying the headline and subhead.
In the first version of my page, the headline is tagged as a headline, and the subhead as a subhead. So Google will think use the uninformative cute headline more than the informative subhead to rank the page.
Now look at this version of the page (the two pages are also linked to each other) and compare the two. The headline and subhead appear completely identical, don’t they? And yet in the second version, the coding is different.
The style sheet on the second page is written in such a way that the text tagged as headline looks like a subhead. This is like telling the search engine “hey, what I am about to say is very important,” and the search engine won’t care what size the text is.
The headline, on the other hand, is made to look the same size as before, but it is not tagged at all, which is like telling the search engine “don’t pay too much attention to me.”
So yes, it’s a good idea to have a keyword-rich, descriptive line to go with your article and to tell Google what it’s about; but that doesn’t mean it has to be the headline of your article. That one can still be cute.
May 10, 2011
Tonight the American Society of Magazine Editors gave Scientific American the 2011 award for general excellence in the category of finance, technology and lifestyle magazines (a hodgepodge of science magazines as well as men’s magazines and business and “active-interest” publications). The other nominees were Backpacker, Bloomberg Markets, GQ and Popular Mechanics.
Through tweets by my colleagues who were at the awards gala tonight, I learned that the award was presented by David Copperfield, who, instead of handing the Ellie to editor-in-chief Mariette DiChristina, made it appear direcly on her table.
SciAm had been nominated for this award as well as for the one for best single-topic issue, which went instead to National Geographic.
April 16, 2011
“Charles Sanders Peirce once observed that in no other branch of mathematics is it so easy for experts to blunder as in probability theory.”
Thus began an article in the October 1959 Scientific American by the celebrated math columnist Martin Gardner. In fact, as John Allen Paulos observed in last January’s issue (“Animal Instincts” [Advances]), humans can sometimes be even worse than pigeons at evaluating probabilities.
Paulos, a mathematician at Temple University in Philadelphia, was describing a notoriously tricky problem known as the Monty Hall paradox. A problem so tricky, in fact, that scores of professional mathematicians and statisticians have stumbled on it over the years. Many have repeatedly failed to grasp it even after they were shown the correct solution.
According to an article by New York Times reporter John Tierney that appeared on July 21, 1991, after a writer called Marilyn vos Savant described the Monty Hall problem—and its uncanny solution—in a magazine the year before, she received something like 10,000 letters, most of them claiming they could prove her wrong. “The most vehement criticism,” Tierney wrote, “has come from mathematicians and scientists, who have alternated between gloating at her (’You are the goat!’) and lamenting the nation’s innumeracy.”
Sure enough, after Paulos mentioned the Monty Hall problem in Scientific American, many readers (though nothing in the order of 10,000) wrote to complain that he had gotten everything wrong, or simply to confess their befuddlement.
“Paulos shows a strange lack of understanding of basic conditional probability,” wrote one reader, “and as a result his article is nonsense.” The reader added that Paulos’s blunder shook his trust in the magazine. “What are your procedures for evaluating submitted papers?” he wrote. This reader was a retired statistics professor.
So we at Scientific American thought it might be worthwhile to try and clarify things a bit. What is this Monty Hall business, and what’s so complicated about it?
The Monty Hall problem was introduced in 1975 by an American statistician as a test study in the theory of probabilities inspired by Monty Hall’s quiz show “Let’s Make a Deal.” (Scholars have observed that the Monty Hall problem was mathematically identical to a problem proposed by French mathematician Joseph Bertrand in 1889—as well as to one, called the three-prisoner game, introduced by Gardner in his 1959 piece; more on that later.) Let’s hear the game’s description from Paulos:
A guest on the show has to choose among three doors, behind one of which is a prize. The guest states his choice, and the host opens one of the two remaining closed doors, always being careful that it is one behind which there is no prize. Should the guest switch to the remaining closed door? Most people choose to stay with their original choice, which is wrong—switching would increase their chance of winning from 1/3 to 2/3. (There is a 1/3 chance that the guest’s original pick was correct, and that does not change.) Even after playing the game many times, which would afford ample opportunity to observe that switching doubles the chances of winning, most people in a recent study switched only 2/3 of the time. Pigeons did better. After a few tries, the birds learn to switch every time.
But wait a minute, you say: after Monty opens the door, there are only two options left. The odds then must be 50-50, or 1/2, for each, so that changing choice of door makes no difference.
To understand what’s going on, we must first make some assumptions, because as it is, the problem’s formulation is ambiguous. So, we shall assume that Monty knows where the car is, and that after the player picks one door he always opens one of the remaining two. Moreover, if the player’s first choice was a door hiding a goat, then Monty always opens the door that hid the other goat; but if the player picked the car, Monty picks randomly between the other two doors, both of which hide a goat.
So imagine you are the player. You take your pick: we’ll call it door 1. One-third of the time, this will be the door with the car, and the remaining 2/3 of the time (66.666… percent) it will be one with a goat. You don’t know what you’ve picked, so you should formulate a strategy that will maximize your overall odds of winning.
Let’s say you picked a goat-hiding door. Monty now opens the other goat-hiding door—call that door 2—and asks you if you want to stick to door 1 or switch to door 3 (which is the one hiding the car). Obviously, in this case by switching you’ll win. But remember, this situation happens 2/3 of the times.
The remaining 1/3 of the time, if you switch, you lose, regardless of which door Monty opens next. But if you adopt the strategy of switching always, no matter what, you’re guaranteed to win 2/3 of the time.
Seems easy enough, doesn’t it? If however you happen to know a little bit of probability theory and you pull out your paper and pencil and start calculating, you might start to doubt this conclusion, as one statistically savvy reader did.
(Warning: this post gets a bit more mathy from here on.)
The reader analyzed the problem using conditional probability, which enables you to answer questions of the type “what are the odds of event A happening given that event B has happened?” The conventional notation for the probability of an event A is P(A), and the notation for “probability of A given B” is P(A | B). The formula to calculate the latter is:
P(A | B) = P(both A and B) / P(B)
The reader wrote:
Let A be the event that the prize is behind door 1 (the initially chosen door), and let B be the event that the prize is not behind door 2 (the door that has been opened). Here, A implies B, so P(both A and B) = P(A) = 1/3, while P(B) = 2/3. Thus P(A | B) = (1/3) / (2/3) = 1/2. Contrary to the claim of Prof. Paulos, nothing is gained by switching from door 1 to door 3. Prof. Paulos is mistaken when he says that P(A | B) = P(A) = 1/3.
What is wrong with this reasoning? It seems utterly plausible and in fact it gave me a headache for about an hour. But it is flawed.
The probability of Monty opening one door or the other changes depending on your initial choice as a player. If you picked a door hiding a goat, Monty has no choice: he is forced to open the door hiding the other goat. If, however, you picked the door hiding the car, Monty has to toss a coin (or some such) before he decides which door to open. But in either case, Monty will open a door that does not hide the prize. Thus, the “event that the prize is not behind door 2 (the door that has been opened)” happens with certainty, meaning P(B) = 1.
Thus, when we apply the formula, we get P(A | B) = (1/3) / (1) = 1/3, not 1/2. The probability that the car is behind door 3 is now 2/3, which means you had better switch.
The Monty Hall paradox is mathematically equivalent to a “wonderfully confusing little problem involving three prisoners and a warden,” the one that Gardner introduced in 1959. Here is Gardner:
Three men—A, B and C—were in separate cells under sentence of death when the governor decided to pardon one of them. He wrote their names on three slips of paper, shook the slips in a hat, drew out one of them and telephoned the warden, requesting that the name of the lucky man be kept secret for several days. Rumor of this reached prisoner A. When the warden made his morning rounds, A tried to persuade the warden to tell him who had been pardoned. The warden refused.
“Then tell me,” said A, “the name of one of the others who will be executed. If B is to be pardoned, give me C’s name. If C is to be pardoned, give me B’s name. And if I’m to be pardoned, flip a coin to decide whether to name B or C.”
“But if you see me flip the coin,” replied the wary warden, “you’ll know that you’re the one pardoned. And if you see that I don’t flip a coin, you’ll know it’s either you or the person I don’t name.”
“Then don’t tell me now,” said A. “Tell me tomorrow morning.” The warden, who knew nothing about probability theory, thought it over that night and decided that if he followed the procedure suggested by A, it would give A no help whatever in estimating his survival chances. So next morning he told A that B was going to be executed.
After the warden left, A smiled to himself at the warden’s stupidity. There were now only two equally probable elements in what mathematicians like to call the “sample space” of the problem. Either C would be pardoned or himself, so by all the laws of conditional probability, his chances of survival had gone up from 1/3 to 1/2.
The warden did not know that A could communicate with C, in an adjacent cell, by tapping in code on a water pipe. This A proceeded to do, explaining to C exactly what he had said to the warden and what the warden had said to him. C was equally overjoyed with the news because he figured, by the same reasoning used by A, that his own survival chances had also risen to 1/2.
Did the two men reason correctly? If not, how should each calculate his chances of being pardoned?
Gardner saved the answer for his next column.
[This post first appeared April 15, 2011 on the Observations blog at ScientificAmerican.com]
April 8, 2011
On April 8, 1911, at the Leiden Cryogenic Laboratory in the Netherlands, Heike Kamerlingh Onnes and his collaborators immersed a mercury capillary in liquid helium and saw the mercury’s electrical resistance drop to nothing once the temperature reached about 3 kelvins, or 3 degrees above absolute zero (around –270 Celsius).
A slide show at ScientificAmerican.com reviews Onnes’s discovery and the milestones that followed it.
This “superconductivity” was one of the first quantum phenomena to be discovered, although back then quantum theory did not exist. In subsequent decades theoreticians were able to put quantum physics on a solid foundation and explain superconductivity. Since then, researchers have discovered new families of materials that superconduct at higher and higher temperatures: the current record-holder works at a balmy 138 K.
So where’s my maglev train?
Indeed, the promise of superconductors—power grids that waste no energy, computers that run at untold gigahertz of speed without overheating and, yes, trains that levitate over magnetic fields—has not fully materialized.
Still, superconductors have made it possible to build the strong magnets that power magnetic resonance imaging machines, which are the most important commercial application of the phenomenon to this day. And scientists use superconductors in advanced experiments every day. For instance, particle accelerators at the Large Hadron Collider in Geneva rely on superconducting coils to generate magnetic fields that steer and focus beams of protons. Some of the most accurate measurements in all of science are done thanks to superconducting quantum interference devices, or SQUIDs.
And finally, superconducting electrical transmission lines are here. Wires based on high-temperature superconductors (with liquid nitrogen–based cryogenics, which are technically simpler and much cheaper than liquid helium–based ones) have recently become commercially available. A South Korean utility plans to install them on a large scale. Some U.S. scientists now say that it may be easier to get permits for and build a national superconducting supergrid than construct a conventional high-voltage system.
April 6, 2011
The American Society of Magazine Editors announced the finalists for the National Magazine Awards yesterday. These awards are also called “Ellies” because the winners receive a reproduction of Calder’s sculpture “Elephant.”
Scientific American got two nominations: one for “General Excellence” in the category of Finance, Technology and Lifestyle Magazines (apparently there is no science category); the other one for best single-topic issue, which mentioned our September 2010 issue “The End”. (The special issue is available as an iPad app, in a single package called “Origins and Endings,” which also includes our September 2009 Origins special issue.)
Congratulations to the entire SciAm staff, and especially to Editor-in-Chief Mariette DiChristina who has shepherded the magazine through a (now we can definitely say) successful relaunch last year. Kudos to Roger Black’s studio for the new design and to our own Design Director Mike Mrak and his staff for making the magazine beautiful month after month. My colleague Michael Moyer deserves special credit for editing the “End” special issue, which included his insightful essay. That issue also included my colleague George Musser’s incredible feature article on whether time could end.
The winners will be announced on May 9.
Over the years, SciAm has earned 16 Ellie nominations and 5 Ellie awards. In addition, in 1999 former Editor-in-Chief was inducted into ASME’s Magazine Editors’ Wall of Fame.
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