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(if you are not familiar with Zipf’s law, you may wish to look at the screenshots first, as they provide a visual context for the following)
Zipfstats is built around Zipf’s law, which states that given some corpus (in this case, a post/page) of natural language, the frequency of any word is inversely proportional to its rank in the frequency table. In a perfect Zipfian distribution, this would mean that the most frequent word in the corpus will occur twice as often as the second most frequent word, three times as often as the third most frequent word and so on. Any given real world corpus, if large enough, will tend to approximate a Zipfian distribution (this also works for cities as ranked by population, though that observation is less useful in this context).
The Zipfstats widget analyzes and reports word frequency by rank of a given single post or page (aka the corpus). The widget shows a small graph that plots the actual frequency-rank distribution of the content against a perfect Zipfian distribution, thus illustrating the degree to which the content follows Zipf’s law. It also provides for a table of the top-ranked words.
Zipfstats only analyzes the core content of a given post/page. It does not incorporate comments into its calculations. By default, it removes shortcode-generated content from its analysis, though you may optionally enable it. Filters, other than do_shortcode() (in the aforementioned case), are not affected in terms of the analysis. Actual output of the original content is unchanged, regardless of the options selected.
Options
Some things to note: