基于语料库的4克研究文章体裁研究

IF 0.1 0 LANGUAGE & LINGUISTICS Estudios de Linguistica-Universidad de Alicante-ELUA Pub Date : 2022-07-19 DOI:10.14198/elua.22267
Eva Lucía Jiménez-Navarro
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引用次数: 0

摘要

在过去的几十年里,对科学专业话语中的短语学的分析引发了研究人员的兴趣,可能是因为在特定的语域中使用单词分组可以提供有关该类型的某些典型特征的信息。例如,Gledhill(2009)研究了科技文章中的时态组合,发现现在时用于定性和经验性表达,而过去时提供定量和研究性描述;passassrez - llantada(2014)对研究文章中的4词词汇束进行了研究,发现这些多词组合表达了参考意义,组织了文本;最后,jimsamnez - navarro(2019)分析了科学论文语料库中的形容词+名词搭配,并得出结论,这些短语单位在这种类型中使用时传达了特定的含义,因为它们代表了研究文章的内容。当前研究的目的是为科学语言中的4克分析做出贡献。为此,确定了两个具体目标:第一,确定4-g的结构;第二,分析它们的功能。该方法基于语料库,包括五个主要步骤:(1)建立专门的研究文章语料库,(2)使用Sketch Engine软件自动提取4-g的列表,(3)手动验证结果列表以抑制不准确的候选列表,(4)根据所选单元的结构框架进行分类,(5)根据所选单元在文本中的功能进行分类。研究结果表明,就第一个目标而言,最典型的4-g是名词短语;至于第二个目标,所检查的顺序主要涉及所进行的研究和文本的作者。总而言之,所确定的4克是特定于研究类型的结构,但也可以用于其他领域。
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A corpus-based study of 4-grams in the research article genre
The analysis of phraseology in the specialized discourse of science has sparked researchers’ interest in the last few decades, probably because the use of word groupings in specific registers can provide information about certain typical features of the genre. For instance, Gledhill (2009) explores colligations of tenses in scientific articles and discovers that the present tense is used for qualitative and empirical expressions, while the past tense provides quantitative and research-oriented descriptions; Pérez-Llantada (2014) investigates 4-word lexical bundles in research articles, finding that these multiword combinations express referential meaning and organize the text; finally, Jiménez-Navarro (2019) analyzes adjective + noun collocations in a corpus of scientific papers and concludes that these phraseological units convey specific meanings when used in this genre, since they represent the contents of research articles. The aim of the current study is to contribute to the analysis of 4-grams in the language of science. To this end, two specific objectives are defined: first, to ascertain the structure of 4-grams; second, to analyze the function they perform. The methodology was based on a corpus and entailed five major steps: (1) a specialized corpus of research articles was built, (2) a list of 4-grams was automatically extracted using the software Sketch Engine, (3) the resulting list was manually verified in order to suppress inaccurate candidates, (4) the selected units were classified depending on their structural framework, and (5) the selected units were categorized according to their function in the text. The findings show that, in terms of the first objective, the most typical 4-grams were noun phrases; and as for the second objective, the sequences examined mostly concerned the research conducted and the authorship of the texts. All in all, the 4-grams identified were structures that were specific to the genre under study but could also be used in other domains.
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