评估单词的通用性

IF 1.6 2区 文学 N/A LANGUAGE & LINGUISTICS International Journal of Corpus Linguistics Pub Date : 2022-11-25 DOI:10.1075/ijcl.21037.eke
Mikkel Ekeland Paulsen
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引用次数: 0

摘要

本文通过对词频和四个离散度度量(“范围”、“卡方”、“比例偏差”和“茱莉兰D”)的交叉验证分析,考察了词的共性、频率和离散度这两个主要语料库指标。该方法提供了命名度量在提取的语言样本中预测语料库项目分布的能力的估计。基于273个挪威语复合词的数据集,结果表明,比例偏差(Deviation of Proportions)是一种鲁棒的离散度量,可以与频率一起使用,以证实基于语料库数据的词共同性断言。此外,离散度量不仅反映了频率统计是从哪种分布生成的,而且还反映了语料库样本中频率估计的可靠性,因为语料库样本给出了语料库样本中语言种类频率的准确表示。
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Assessing word commonness
The article investigates the two main corpus indicators of word commonness, frequency and dispersion, through a cross-validation analysis of frequency and four dispersion measures (‘Range’, ‘Chi-squared’, ‘Deviation of Proportions’ and ‘Juilland’s D’). The approach provides an estimation of the capacity of the named measures to predict the distribution of corpus items in an extracted language sample. Based on a dataset of 273 Norwegian compounds, the results show that especially Deviation of Proportions is a robust measure of dispersion that can be used in conjunction with frequency to substantiate assertions of word commonness based on corpus data. In addition, dispersion measures do not only reflect what sort of distribution the frequency statistic is generated from, but also how reliable the frequency estimation in the corpus sample is in terms of giving an accurate representation of frequency in the language variety that the corpus is sampled from.
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来源期刊
CiteScore
3.30
自引率
0.00%
发文量
43
期刊介绍: The International Journal of Corpus Linguistics (IJCL) publishes original research covering methodological, applied and theoretical work in any area of corpus linguistics. Through its focus on empirical language research, IJCL provides a forum for the presentation of new findings and innovative approaches in any area of linguistics (e.g. lexicology, grammar, discourse analysis, stylistics, sociolinguistics, morphology, contrastive linguistics), applied linguistics (e.g. language teaching, forensic linguistics), and translation studies. Based on its interest in corpus methodology, IJCL also invites contributions on the interface between corpus and computational linguistics.
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