Mathematical Linguistics
Online ISSN : 2433-0302
Print ISSN : 0453-4611
Volume 31 , Issue 1
Showing 1-5 articles out of 5 articles from the selected issue
Paper B
  • Analysis of Words and Component Characters Based on a Corpus
    Yumiko Honda
    Type: Paper B
    2017 Volume 31 Issue 1 Pages 1-19
    Published: June 20, 2017
    Released: August 01, 2018
    JOURNALS OPEN ACCESS
    This paper aims to show the quantitative transparency tendency of two-character Sino-Japanese words and to obtain useful information for teaching Japanese language through a survey and analysis of high frequency words in the written language. The transparency degree of two-character Sino-Japanese words is divided into three groups: transparent, half-transparent, and opaque. For examining transparency, descriptions of words in Japanese dictionaries are used to retain the objectivity of examining. The survey results indicate the following: 1. Each group accounts for a ratio of high frequency words; 2. The ratio of transparent words is higher in the intermediate and above intermediate levels than in the elementary level for words appearing in the Japanese-Language Proficiency Test. However, the ratio of opaque words is higher in the elementary level than in the intermediate and above intermediate levels. 3. The survey results obtained from using description of words in Japanese dictionaries have similarities to those obtained from using questionnaires to Japanese university students. Therefore, in this paper, the quantitative transparency tendency is useful information for teachers in considering contents of teaching two-character Sino-Japanese words.
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  • Katsuo Tamaoka
    Type: Paper B
    2017 Volume 31 Issue 1 Pages 20-35
    Published: June 20, 2017
    Released: August 01, 2018
    JOURNALS OPEN ACCESS
    Newspapers articles are written by reporters for the general public, so provide accurate information using simple standard expressions. However, it is not clear whether written texts in newspapers reflect typical language production by native speakers. It is assumed that mature native Japanese speakers produce various sound-symbolic words—such as onomatopoeia and mimesis, which are cultivated through childhood experience—with various related verbs. The present study investigated the similarities of collocation patterns for 28 different sound-symbolic words co-occurring with verbs, by comparing nine years of Asahi Newspaper articles (1991-99) with verbal production by 36 native Japanese speakers within 30 seconds. No significant differences were found in either the variation criterion of entropy or the regularity criterion of redundancy for collocational patters between newspaper corpus and native speakers’ production. The result indicated a great similarity between newspaper corpus and native speakers. Exceptional words were only found in 4 out of 28 sound-symbolic words from the descriptive perspective.
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Resource
  • Koichi Higuchi
    Type: Resource
    2017 Volume 31 Issue 1 Pages 36-45
    Published: June 20, 2017
    Released: August 01, 2018
    JOURNALS OPEN ACCESS
    The author introduces how to perform statistical analysis of textual data in an automated and effective way by utilizing a free software “KH Coder” in the field of linguistics. First, the major functionalities and philosophy of the KH Coder are explained to provide an overview of the software. The KH Coder was originally developed to perform analysis in the field of sociology or social research rather than that of linguistics. Because the KH Coder was developed in a different discipline, this overview will help with understanding its function and how to actually use it as applied to linguistics. Second, procedures for customizing the KH Coder settings are described to demonstrate how it will be more useful in the field of linguistics. For example, with the default settings, the KH Coder ignores all function words such as particles or auxiliary verbs, and focuses only on content words. To analyze function words, the parts of speech setting needs to be modified. Additionally, we can modify the word extraction setting to manually correct morphological analysis results to increase their accuracy.
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