Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data
The aim of the work is to make a comparative analysis of the associative links of full-meaning words from the upper zone of the frequency list, compiled on the basis of a research corpus of blog texts in Russian, in a psycholinguistic experiment and the distributivesemantic model Global Vectors (Glo...
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| Format: | Article |
| Language: | Russian |
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Tsentr nauchnykh i obrazovatelnykh proektov
2022-06-01
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| Series: | Научный диалог |
| Subjects: | |
| Online Access: | https://www.nauka-dialog.ru/jour/article/view/3852 |
| _version_ | 1797245629644144640 |
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| author | T. A. Litvinova E. S. Kotlyarova V. A. Zavarzina |
| author_facet | T. A. Litvinova E. S. Kotlyarova V. A. Zavarzina |
| author_sort | T. A. Litvinova |
| collection | DOAJ |
| description | The aim of the work is to make a comparative analysis of the associative links of full-meaning words from the upper zone of the frequency list, compiled on the basis of a research corpus of blog texts in Russian, in a psycholinguistic experiment and the distributivesemantic model Global Vectors (GloVe), trained on this corpus. The relevance of the work is due to the need for a comprehensive study of the psychologically relevant meaning of the word. The novelty of the study lies in the fact that such an analysis is carried out taking into account the gender factor of the respondent / author of the text. The use of a set of methods for data mining (clustering, classification) and visualization of its results made it possible to establish the influence of gender on the composition of the semantic associates of the analyzed words (that is, words with close vectors in the distributive-semantic model) and the absence of such an effect in their associates recorded in the associative dictionary. As the study showed, distributivesemantic models and dictionary associative norms reflect different aspects of the psychologically relevant content of the word and should be used as complementary sources when modeling the psychologically relevant meaning of the word, taking into account the individual characteristics of the speaker, while conducting such an analysis it is advisable to use data mining methods. |
| first_indexed | 2024-03-08T04:28:13Z |
| format | Article |
| id | doaj.art-8091df1832a34817a5ee206749bf4935 |
| institution | Directory Open Access Journal |
| issn | 2225-756X 2227-1295 |
| language | Russian |
| last_indexed | 2024-04-24T19:29:57Z |
| publishDate | 2022-06-01 |
| publisher | Tsentr nauchnykh i obrazovatelnykh proektov |
| record_format | Article |
| series | Научный диалог |
| spelling | doaj.art-8091df1832a34817a5ee206749bf49352024-03-25T14:31:08ZrusTsentr nauchnykh i obrazovatelnykh proektovНаучный диалог2225-756X2227-12952022-06-0111513615610.24224/2227-1295-2022-11-5-136-1562216Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model DataT. A. Litvinova0E. S. Kotlyarova1V. A. Zavarzina2Voronezh State Pedagogical UniversityVoronezh State Pedagogical UniversityVoronezh State Pedagogical UniversityThe aim of the work is to make a comparative analysis of the associative links of full-meaning words from the upper zone of the frequency list, compiled on the basis of a research corpus of blog texts in Russian, in a psycholinguistic experiment and the distributivesemantic model Global Vectors (GloVe), trained on this corpus. The relevance of the work is due to the need for a comprehensive study of the psychologically relevant meaning of the word. The novelty of the study lies in the fact that such an analysis is carried out taking into account the gender factor of the respondent / author of the text. The use of a set of methods for data mining (clustering, classification) and visualization of its results made it possible to establish the influence of gender on the composition of the semantic associates of the analyzed words (that is, words with close vectors in the distributive-semantic model) and the absence of such an effect in their associates recorded in the associative dictionary. As the study showed, distributivesemantic models and dictionary associative norms reflect different aspects of the psychologically relevant content of the word and should be used as complementary sources when modeling the psychologically relevant meaning of the word, taking into account the individual characteristics of the speaker, while conducting such an analysis it is advisable to use data mining methods.https://www.nauka-dialog.ru/jour/article/view/3852association experimentdistributive semanticsdistributive-semantic modelcorpus of textsdata mining |
| spellingShingle | T. A. Litvinova E. S. Kotlyarova V. A. Zavarzina Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data Научный диалог association experiment distributive semantics distributive-semantic model corpus of texts data mining |
| title | Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data |
| title_full | Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data |
| title_fullStr | Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data |
| title_full_unstemmed | Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data |
| title_short | Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data |
| title_sort | gender factor in associative links of words dictionary and distributive semantic model data |
| topic | association experiment distributive semantics distributive-semantic model corpus of texts data mining |
| url | https://www.nauka-dialog.ru/jour/article/view/3852 |
| work_keys_str_mv | AT talitvinova genderfactorinassociativelinksofwordsdictionaryanddistributivesemanticmodeldata AT eskotlyarova genderfactorinassociativelinksofwordsdictionaryanddistributivesemanticmodeldata AT vazavarzina genderfactorinassociativelinksofwordsdictionaryanddistributivesemanticmodeldata |