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SherlockHolmes (version 1.0.2)

Building a Concordance of Terms in a Series of Texts

Description

Compute the frequency distribution of a search term in a series of texts. For example, Arthur Conan Doyle wrote a total of 60 Sherlock Holmes stories, comprised of 54 short stories and 4 longer novels. I wanted to test my own subjective impression that, in many of the stories, Sherlock Holmes' popularity was used as bait to induce the reader to read a story that is essentially not primarily a Sherlock Holmes story. I used the term "Holmes" as a search pattern, since Watson would frequently address him by name, or use his name to describe something that he was doing. My hypothesis is that the frequency distribution of the search pattern "Holmes" is a good proxy for the degree to which a story is or is not truly a Sherlock Holmes story. The results are presented in a manuscript that is available as a vignette and online at .

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Version

Install

install.packages('SherlockHolmes')

Monthly Downloads

153

Version

1.0.2

License

GPL (>= 2)

Maintainer

Barry Zeeberg

Last Published

November 30th, 2025

Functions in SherlockHolmes (1.0.2)

csw

Sherlock data sets
freqHist

freqHist
coChronology

coChronology
freqs

Sherlock data sets
chronology

chronology
Sherlock

Sherlock
retrieveLmStats

retrieveLmStats
readTitles

readTitles
distributions

distributions
starts

Sherlock data sets
strSplitTab

strSplitTab
patterns

Sherlock data sets
plot_dpseg2

plot_dpseg2
texts

Sherlock data sets
texts.vec

Sherlock data sets
segs

Sherlock data sets
startLine

startLine
outside

Sherlock data sets
mergeTables

mergeTables
contingency

contingency
frequency

frequency
csp

Sherlock data sets
grabFunctionParameters

grabFunctionParameters
concordance

concordance
titles

Sherlock data sets
titles.vec

Sherlock data sets
segments

segments
rolling

rolling
inside

Sherlock data sets
lengths

lengths