{"title":"To Move or Not to Move: An Entropy-based Approach to the Informativeness of Research Article Abstracts across Disciplines","authors":"Wei Xiao, Li Li, Jin Liu","doi":"10.1080/09296174.2022.2037275","DOIUrl":null,"url":null,"abstract":"ABSTRACT Research article (RA) abstracts succinctly and skilfully epitomize the core information of the full text and have thus attracted the attention of a number of scholars. While previous studies mainly focused on the rhetorical structures, meta-discursive features and lexico-grammatical features, few have made explorations from the perspective of information theory. To bridge this gap, the present study conducted an entropy-based analysis to explore the distribution pattern of information content across moves and the variations across disciplines. 318 RA abstracts across the natural sciences, social sciences and humanities (106 abstracts per discipline) were selected and three indices, i.e. the 1-/ 2-/ 3-gram entropies, were used to examine whether different indices yielded different features. The results show that in an RA abstract, the information content is unevenly distributed across moves; different entropy indices may reflect different linguistic properties; and both similarities and variations exist in information content across disciplines. These phenomena can be attributed to the functions of moves, the linguistic meanings of indices and disciplinary features. This study has implications for RA abstract writing instruction and practice, as well as for broadening the applications of quantitative linguistic methods into less touched fields.","PeriodicalId":45514,"journal":{"name":"Journal of Quantitative Linguistics","volume":"30 1","pages":"1 - 26"},"PeriodicalIF":0.7000,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quantitative Linguistics","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/09296174.2022.2037275","RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 3
Abstract
ABSTRACT Research article (RA) abstracts succinctly and skilfully epitomize the core information of the full text and have thus attracted the attention of a number of scholars. While previous studies mainly focused on the rhetorical structures, meta-discursive features and lexico-grammatical features, few have made explorations from the perspective of information theory. To bridge this gap, the present study conducted an entropy-based analysis to explore the distribution pattern of information content across moves and the variations across disciplines. 318 RA abstracts across the natural sciences, social sciences and humanities (106 abstracts per discipline) were selected and three indices, i.e. the 1-/ 2-/ 3-gram entropies, were used to examine whether different indices yielded different features. The results show that in an RA abstract, the information content is unevenly distributed across moves; different entropy indices may reflect different linguistic properties; and both similarities and variations exist in information content across disciplines. These phenomena can be attributed to the functions of moves, the linguistic meanings of indices and disciplinary features. This study has implications for RA abstract writing instruction and practice, as well as for broadening the applications of quantitative linguistic methods into less touched fields.
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.