Methodology for Trend Research Analysis: Problem Statement
https://doi.org/10.21603/sibscript-2025-27-4-656-666
Abstract
If free associative experiments are separated in time, they require a separate methodology. Previous results mean an opportunity for a trend study, provided that the first experiment is replicated under the same conditions and with similar subjects in terms of age and gender. The quantitative analysis of experimental data needs an efficient method of semantic analysis to process the reactions and associative fields. The author developed and tested a new methodology for analyzing the same-name associative fields based on two associative experiments (2002 and 2022). To obtain a reliable trend study, the second experiment recreated the conditions of the first one, i.e., stimuli (112 words), subjects (500 people), written form, etc. A. A. Grigoriev and M. S. Klenskaya’s methodology for quantitative assessment of associative fields made it possible to analyze the same-name associative fields separated in time. The qualitative analysis involved Yu. N. Karaulov’s semantic gestalt methodology, which yielded a semantic field model based on the same-name reactions with a distinct core periphery structure. It was modified by using the quantitative method for relative frequencies of both individual reactions and gestalt zones, i.e., semantic classes.
About the Author
Elena N. Guts
Dostoevsky Omsk State University
Russian Federation
Competing Interests:
Russian Federation
Scopus Author ID: 57224590632
Omsk
Competing Interests:
The author declared no potential conflict of interests regarding the research, authorship, and / or publication of this article
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Guts E.N. Methodology for Trend Research Analysis: Problem Statement. SibScript. 2025;27(4):656-666. (In Russ.) https://doi.org/10.21603/sibscript-2025-27-4-656-666
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