present (or, for that matter, from the common noun “a bet”). - the verb is not a compound, like “overpay” or “unbind”, as the effect of the underlying verb (“pay”, “bind”) is presumably stronger than that of usage frequency.
We therefore obtain a list of 106 verbs that we use in the study (marked by the denomination ‘True’ in the column “Use in the study?”)
III.5B. Verb frequencies
Next, for each verb, we computed the frequency of the regular past tense (built by suffixation of ‘-ed’ at the end of the verb), and the frequency of the irregular past tense (summing preterit and past participle). These trajectories are represented in Fig 3A and Fig S8.
We define the regularity of a verb: at any given point in time, the regularity of a verb is the percentage of past tense usage made using the regular version. Therefore, in a given year, the regularity of a verb is r=R/(R+l) where R is the number of times the regular past tense was used, and | the number of times the irregular past tense was used. The regularity is a continuous variable that ranges between 0 and 1 (100%).
We plot in Figure 3B the mean regularity between 1800-1825 in x-axis, and the mean regularity between 1975-2000 in y-axis.
If we assume that a speaker of the English language uses only one of the two variants (regular or irregular); and that all speakers of English are equally likely to use the verb; then the regularity translates directly into percentage of the population of speakers using the regular form. While these assumptions may not hold generally, they provide a convenient way of estimating the prevalence of a certain word in the population of English speakers (or writers).
III.5C. Rates of regularization
We can compute, for any verb, the slope of regularity as a function of time: this can be interpreted as the variation in percentage of the population of English speakers using the regular form.
By holding population size constant over the time window used to obtain the slope, we derive the variation of population using the regular form in absolute terms.
For instance, the regularity of “sneak/snuck” has decreased from 100% to 50% over the past 50 years, which is 1% per year. We consider the population of US English speakers to be roughly 300 million. As a result, snuck is sneaking in at a speed of 3 million speakers per year, or about one speaker per minute in the US.
III.5D. Classification of Verbs
The verbs were classified into different types based on the phonetic pattern they represented using the classification of Ref 18 (main text). Fig 3C shows the median regularity for the verbs ‘burn’, ‘spoil’, ‘dwell’, ‘learn’, ‘smell’, ‘spill’ in each year. We compute the UK rate as above, using 60 million for UK population.
III.6. Collective Memory
One hundred timelines were generated, for every year between 1875 and 1975. Amplitude for each plot was measured by either computing ‘peak height’ — i.e., the maximum of all the plotted values, or ‘area- under-the curve’ — j.e., the sum of all the plotted values. The peak for year X always occurred within a
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