{"title":"基于语料库的名词在语域和学科中的分布研究","authors":"Yiyang Hu, Qingshun He","doi":"10.1080/09296174.2023.2209487","DOIUrl":null,"url":null,"abstract":"ABSTRACT Adnominals are an important resource of noun modification in written registers, especially in academic writing. This study compares the frequencies of adjectival adnominals and nominal adnominals across two registers (Fiction and Academic writing) by calculating T-values and conducting Welch’s t-tests on the adnominal subtypes. It is found that the preference for nominal adnominals exists in both the two registers and the mean frequencies of adjectival adnominals, premodifying nouns and postmodifying nouns increase as the register moves from Fiction to Academic writing. We further investigate the frequencies of adnominals in the research article abstracts across three disciplinary groups by conducting Welch’s ANOVA test. No significant difference is revealed in T-values in the research article abstracts across disciplines. The difference of adjectival adnominals, nouns as postmodifiers and appositive nouns lacks practical applications, while the effects of disciplines on the frequency of premodifying nouns cannot be rejected. It is the mean frequencies of premodifying nouns that show the significant difference in the research article abstracts across disciplines. Premodifying nouns are more prevalent in hard science texts than in soft science texts.","PeriodicalId":45514,"journal":{"name":"Journal of Quantitative Linguistics","volume":"30 1","pages":"183 - 203"},"PeriodicalIF":0.7000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Corpus-Based Study of the Distributions of Adnominals Across Registers and Disciplines\",\"authors\":\"Yiyang Hu, Qingshun He\",\"doi\":\"10.1080/09296174.2023.2209487\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Adnominals are an important resource of noun modification in written registers, especially in academic writing. This study compares the frequencies of adjectival adnominals and nominal adnominals across two registers (Fiction and Academic writing) by calculating T-values and conducting Welch’s t-tests on the adnominal subtypes. It is found that the preference for nominal adnominals exists in both the two registers and the mean frequencies of adjectival adnominals, premodifying nouns and postmodifying nouns increase as the register moves from Fiction to Academic writing. We further investigate the frequencies of adnominals in the research article abstracts across three disciplinary groups by conducting Welch’s ANOVA test. No significant difference is revealed in T-values in the research article abstracts across disciplines. The difference of adjectival adnominals, nouns as postmodifiers and appositive nouns lacks practical applications, while the effects of disciplines on the frequency of premodifying nouns cannot be rejected. It is the mean frequencies of premodifying nouns that show the significant difference in the research article abstracts across disciplines. Premodifying nouns are more prevalent in hard science texts than in soft science texts.\",\"PeriodicalId\":45514,\"journal\":{\"name\":\"Journal of Quantitative Linguistics\",\"volume\":\"30 1\",\"pages\":\"183 - 203\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Quantitative Linguistics\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1080/09296174.2023.2209487\",\"RegionNum\":2,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"LANGUAGE & LINGUISTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quantitative Linguistics","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/09296174.2023.2209487","RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
A Corpus-Based Study of the Distributions of Adnominals Across Registers and Disciplines
ABSTRACT Adnominals are an important resource of noun modification in written registers, especially in academic writing. This study compares the frequencies of adjectival adnominals and nominal adnominals across two registers (Fiction and Academic writing) by calculating T-values and conducting Welch’s t-tests on the adnominal subtypes. It is found that the preference for nominal adnominals exists in both the two registers and the mean frequencies of adjectival adnominals, premodifying nouns and postmodifying nouns increase as the register moves from Fiction to Academic writing. We further investigate the frequencies of adnominals in the research article abstracts across three disciplinary groups by conducting Welch’s ANOVA test. No significant difference is revealed in T-values in the research article abstracts across disciplines. The difference of adjectival adnominals, nouns as postmodifiers and appositive nouns lacks practical applications, while the effects of disciplines on the frequency of premodifying nouns cannot be rejected. It is the mean frequencies of premodifying nouns that show the significant difference in the research article abstracts across disciplines. Premodifying nouns are more prevalent in hard science texts than in soft science texts.
期刊介绍:
The Journal of Quantitative Linguistics is an international forum for the publication and discussion of research on the quantitative characteristics of language and text in an exact mathematical form. This approach, which is of growing interest, opens up important and exciting theoretical perspectives, as well as solutions for a wide range of practical problems such as machine learning or statistical parsing, by introducing into linguistics the methods and models of advanced scientific disciplines such as the natural sciences, economics, and psychology.