Abstract
A set of identity words serves as data points for three approaches to analyzing meanings: (1) dictionary definitions; (2) a word’s collocates or nearby words; (3) word associations. In each approach, function words and other words with low semantic content are removed, and remaining words are converted to root forms to obtain a list of keywords constituting an identity explication. The lists are turned into a zero-one matrix with a column for each identity and a row for each keyword used in any definition. Mathematical manipulations result in a correlation matrix showing the extent of keyword overlap in the definitions, and this is the basis of a principal component analysis defining clusters of identities in terms of similarities in their explications.
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Heise, D. (2019). Analyzing Meanings of Identities. In: Cultural Meanings and Social Institutions. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-03739-0_2
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DOI: https://doi.org/10.1007/978-3-030-03739-0_2
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