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COMPUTING SCIENCE

Bit Lit

With digitized text from five million books, one is never at a loss for words

Brian Hayes

The Book of Numbers

2011-05HayesFC.jpgClick to Enlarge ImageOn looking at the numbers included in the n-gram archive, I was surprised at first by their abundance. Of the 7.4 million unique 1-grams, about 7 percent are numbers or numberlike strings of digits. But the explanation is straightforward: Numbers have higher entropy than words. Only a tiny fraction of all possible sequences of letters make a meaningful word, but almost any combination of digits is a properly formed number. Thus for a given total quantity of numbers, we can expect to find greater variety.

To look more closely at the numeric 1-grams, I had to decide exactly what I would accept as a number. The OCR system allows mixed strings of letters and digits (1Deut, Na2SO4), but I wanted to consider just “pure” numbers, those that denote a definite numeric value or magnitude. I decided to accept any sequence of characters consisting entirely of digits or digits with a single embedded decimal point. The OCR program also accepts numbers preceded by a “$” sign, so I collected those dollar amounts too, but in a separate file.

Many different numerals can represent the same number: 01, 1, 1.0, 1.00 and 1.000 are all listed separately in the 1-gram files, but they all designate the same mathematical magnitude. I consolidated these items under the canonical value 1.0, and merged their yearly occurrence data into a single record. This procedure is not without drawbacks, in that it treats as numbers some items that aren’t meant to designate a numeric value, such as Zip codes. But I don’t know how to weed out those items.

The number list I compiled has 458,794 unique values. The smallest is necessarily 0, since the OCR process strips away any minus signs. What’s the largest entry? It’s the number formed by repeating the digit 7 exactly 80 times. When I looked up the origin of this curious value, I discovered images of computer punch cards, with labeled rows of 80 columns.

The first thing I did with the numbers was check to see if they obey Benford’s law, which describes the distribution of first digits in most of the numbers we meet in everyday life, such as those in stock-market tables. The law predicts that 1 is the most common leading digit, with higher digit values getting progressively rarer. In the theoretical distribution the frequency of digit d is proportional to log10(1+1/d).

When I tested the 1-gram numbers against the predictions of Benford’s law, the result was inconclusive. As expected, smaller first-digit values are more common among the 1-grams, but the preference for 1 is even more exaggerated than the Benford distribution predicts. The first digit should be a 1 about 30 percent of the time, but the actual frequency is 43 percent. Maybe those Zip codes are causing trouble?

2011-05HayesFD.jpgClick to Enlarge ImageI have another hypothesis: The distortion is caused by the times we live in! High on the list of popular numbers are values that look like years, almost all of which begin with 1. Numbers such as 2000, 1990, 1992 and 1980 are roughly 100 times more frequent than other four-digit numbers. To test my hypothesis I created an altered data set in which all numbers in the range 1800–1999 have their frequency artificially reduced by a factor of 1/100. The result is considerably closer to the Benford distribution, with 1 having a frequency of 34 percent (see illustration at right).

Something else revealed by this collection of numeric data is the extraordinary human fondness for round numbers. The illustration at the top of this page plots the abundance of the first 100 integers. For the most part, frequency decreases with increasing magnitude, but numbers that are “rounder”—divisible by 10, or if not by 10 then by 5—stand out above the crowd. (Also note that the integers 7 and 11, which by some vague measure might be taken as the least round numbers, are curiously depressed.)

Dollar amounts are even more dramatically biased in favor of well-rounded numbers. I had expected the monetary subset to be full of numbers ending in 99. Maybe that will be the case if we ever get an archive of junk mail and supermarket advertising, but in books there’s a distinct preference for trailing zeros. The most popular dollar amounts are 1, 100, 2, 5, 10, 1000, 10000.








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