A corpus based analysis of lexical richness of Beijing Mandarin speakers
Variable Identification and Model Construction
Bibliographic Data
| ID | 7900659 |
|---|---|
| Authors | Yanhui Zhang (0000-0002-8383-1760, Chinese University of Hong Kong, corresponding author) |
| Year | 2014 |
| Volume | 44 |
| Pages | 60-69 |
| Publication date | 2014-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Language Sciences (JOURNAL) |
| Journal identifiers | ISSN: 0388-0001 • E-ISSN: 1873-5746 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.langsci.2013.12.003 |
| OpenAlex | W1974897390 |
| Language | EN |
| Citations received | 4 |
| References cited | 20 |
This work concerns the lexical richness of Beijing Mandarin speakers measured by entropy. The data used for the study are the Beijing Mandarin Spoken Corpora, a conversational and spontaneous speech corpus of contemporary Beijing Mandarin speakers. Based on the sociovariational linguistic hypotheses and data analysis, the study attempts to identify and explain the key demographical and socioeconomic parameters that impact the entropy of each subject’s spoken texts. Both one-dimensional and multi-dimensional statistical models are proposed to quantify the relationships between the pertinent measure of lexical richness and the prominent indicative variables, including age, level of education, and profession premium. A multi-dimensional nonlinear model encompassing these findings is designed and calibrated with statistical estimation methods. Possible future directions and applications in relevant field of applied linguistics are provided
Beijing · Corpus linguistics · Geography · Linguistics · Mandarin Chinese · Natural language processing · Authorship Attribution and Profiling · Computer Science · Linguistic Variation and Morphology · Natural Language Processing Techniques · Psychology · Artificial Intelligence
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| Unique citing works | 4 |
|---|---|
| Citations per year | 0,8 |
| Citation span | 2021 - 2023 (3) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 4 |