Quantitative linguistics approach to interlanguage development: a study based on the Guangwai-Lancaster Chinese Learner Corpus

Lingua ◽  
2019 ◽  
Vol 230 ◽  
pp. 102736 ◽  
Author(s):  
Heng Chen ◽  
Hai Xu
2015 ◽  
Author(s):  
Maolin Wang ◽  
Shervin Malmasi ◽  
Mingxuan Huang

Corpora ◽  
2012 ◽  
Vol 7 (1) ◽  
pp. 69-90 ◽  
Author(s):  
Andrew Wilson

Contemporary depth psychology is under constant pressure to demonstrate and strengthen its evidence base. In this paper, I show how the analysis of large corpora can contribute to this goal of developing and testing depth-psychological theory. To provide a basis for evaluating statements about foot and shoe fetishism, I analyse the thirty-six most frequent three-word phrases (or trigrams) in a corpus of about 1.6 million words of amateur fetish stories written in the German language. Zipfian methods from quantitative linguistics are used to specify the number of phrases for analysis and I argue that these reflect the core themes of the corpus. The analysis reveals three main dimensions. First, it corroborates the observations of the early sexologists that foot and shoe fetishism is very closely intertwined with sadomasochism. Secondly, it shows that genitalia-related phrases are also common, but an examination of their contexts questions Freud's theory that fetishism results from an assumption of female castration. Thirdly, it reveals that the mouth also plays a key role; however, the frequent co-presence of genitalia references in the same texts does not seem to support straightforwardly the most common alternative theory of fetishism based on object relations. Future research could valuably extend this approach to other fetishes and, in due course, to other depth-psychological constructs.


Author(s):  
Inga Kaija

A Latvian learner corpus “LaVA” is being built in the Institute of Mathematics and Computer Science, University of Latvia. The corpus includes texts written by beginner learners in the first two semesters of learning Latvian as a foreign language. The texts are written by hand and digitized afterwards in order to reduce the issues that could be caused by the necessity to learn not only writing itself but also using a foreign keyboard. One of the features that cannot be digitized is the new letters created by adding diacritical marks which are not used that way in the standard Latvian alphabet. Since one of the essential steps in learning to write in a language is learning the letters and diacritical marks of that language, this study aims to find instances of such newly made letters and to discuss the basic quantitative measures in order to define hypotheses and areas of interest for further research of such usage. Altogether 322 texts were searched, and 175 examples were found. The amount of examples found in 2nd semester texts was less than half the amount of examples found in the 1st semester texts, but the percentage of texts containing examples was higher than expected – more than 33 % in the 1st semester and almost 20 % in the 2nd semester. It leads to a conclusion that this is quite a common occurrence but also prone to reduction in the second semester. The corpus does not provide any data on later semesters so it cannot be predicted when such instances should become a rare, individual feature rather than a common one. The average amount of examples in a text is not high, though. Counting only the texts where at least one example was found, the average amount of examples per text is 2.136 in the 1st semester and 1.690 in the 2nd semester. Considering that the absolute lowest possible value here is 1, it should not be considered as a high value. Therefore, using diacritical marks to make new letters, while a common feature of the Latvian interlanguage, could be characterized as casual rather than systemic. However, that does not exclude the possibility of certain patterns in usage. The currently collected data already shows that there are some words – such as garšo, viņš, ļoti, četri – where examples were found in more than one author’s text. Examples of using unsuitable diacritical marks are also sometimes found next to letters for which said diacritical marks would be suitable. This should be explored more thoroughly using qualitative methods. The size of the corpus keeps growing; the expected size upon completion is 1000 texts. When it is reached, it would be useful to repeat the study and check whether the larger amount of data still confirms the same assumptions. The larger sample size would also allow for more detailed quantitative analysis discussing each letter, diacritical mark, placement of the diacritical mark, and metadata collected for the corpus, such as gender, native language and other spoken languages by the authors of the texts.


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