ERA

Download the full-sized PDF of Topic marking in a Shanghainese corpus: From observation to predictionDownload the full-sized PDF

Analytics

Share

Permanent link (DOI): https://doi.org/10.7939/R3FF3M347

Download

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Linguistics, Department of

Collections

This file is in the following collections:

Research Publications (Linguistics)

Topic marking in a Shanghainese corpus: From observation to prediction Open Access

Descriptions

Author or creator
Arppe, Antti
Han, Weifang
Newman, John
Additional contributors
Subject/Keyword
probabilities
polytomous logistic regression
Chinese dialect
statistical analysis
topic marking
Shanghainese
Type of item
Journal Article (Published)
Language
English
Place
Time
Description
Shanghainese is an extremely topic-prominent language with many topic markers in competition with one another, often without any obvious basis for the selection of one topic marker over another. We explore the influence of five variables on the five most frequent topic markers in a corpus of (spoken) Shanghainese: topic length, syntactic category of the topic, function of the topic, comment type, and genre. We carry out a multivariate statistical analysis of the data, relying on a polytomous logistic regression model. Our approach leads to a satisfying quantification of the role of each factor, as well as an estimate of the probabilities of combinations of factors, in influencing the choice of topic marker. This study serves simultaneously as an introduction to the polytomous package (Arppe 2013) in the statistical software package R.
Date created
2013
DOI
doi:10.7939/R3FF3M347
License information
Rights
© 2013 Antti Arppe, Weifang Han & John Newman. This version of this article is open access and can be downloaded and shared. The original author(s) and source must be cited.
Citation for previous publication
Han, W., A. Arppe, & J. Newman. 2013. Topic marking in a Shanghainese corpus: From observation to prediction. Corpus Linguistics and Linguistic Theory.1-29.
Source
Link to related item

File Details

Date Uploaded
Date Modified
2015-07-14T20:54:30.039+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 719266
Last modified: 2015:10:12 14:46:44-06:00
Filename: CLLT_2013_1.pdf
Original checksum: 119af929210a0e0da499c602b80382f9
Well formed: true
Valid: true
Page count: 30
Activity of users you follow
User Activity Date