Abstract
In a semantic text analysis the researcher begins by creating one of two types of semantic grammars, each of which provides one or more templates that specify the ways concepts (or more general themes) may be related. On the one hand, a phenomenal semantic grammar can be created to extract phenomenon-related information from a text population (e.g., “Among the population's grievances [the phenomenon of interest in this case], which were ones for the abolition of taxes?”). On the other hand, a generic semantic grammar may be developed to yield data about the text population itself (e.g., “Among all clauses in the text population, how many were grievances for the abolition of taxes?”). This paper describes a generic semantic grammar that can be used to encode themes and theme relations in every clause within randomly sampled texts. Unlike the surface-grammatical relations mapped by syntax grammars, the theme relations allowed in this grammar only permit unambiguous encoding according to the meanings that clauses were intended to convey within their social context. An application of the grammar provides a concrete illustration of its research potential
Subject
Sociology and Political Science
Cited by
20 articles.
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