移动还是不移动:基于熵的跨学科研究论文摘要信息性方法

IF 0.7 2区 文学 0 LANGUAGE & LINGUISTICS
Wei Xiao, Li Li, Jin Liu
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引用次数: 3

摘要

摘要研究文章简明扼要地概括了全文的核心信息,吸引了许多学者的注意。虽然以往的研究主要集中在修辞结构、元话语特征和词典语法特征上,但很少有人从信息论的角度进行探索。为了弥补这一差距,本研究进行了基于熵的分析,以探索信息内容在不同动作中的分布模式以及不同学科之间的差异。选择了318篇自然科学、社会科学和人文学科的RA摘要(每个学科106篇摘要),并使用三个指数,即1-/2-/3-克熵,来检查不同的指数是否产生不同的特征。结果表明,在RA摘要中,信息内容在不同动作中分布不均匀;不同的熵指数可以反映不同的语言特性;跨学科的信息内容既有相似之处,也有差异。这些现象可归因于动作的功能、指标的语言意义和学科特征。这项研究对RA抽象写作的指导和实践,以及将定量语言学方法扩展到较少涉及的领域都有意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
To Move or Not to Move: An Entropy-based Approach to the Informativeness of Research Article Abstracts across Disciplines
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.
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来源期刊
CiteScore
2.90
自引率
7.10%
发文量
7
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.
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