Text-mining open-ended survey responses using structural topic modeling: A practical demonstration to understand parents' coping methods during the COVID-19 pandemic in Singapore

Please use this identifier to cite or link to this item: https://doi.org/10.1080/15228835.2022.2036301

Title:	Text-mining open-ended survey responses using structural topic modeling: A practical demonstration to understand parents' coping methods during the COVID-19 pandemic in Singapore
Authors:	Gerard Chung Maria Rodriguez Paul Lanier Daniel Gibbs
Issue Date:	14-Feb-2022
Publisher:	Taylor & Francis
Citation:	Gerard Chung, Maria Rodriguez, Paul Lanier, Daniel Gibbs (2022-02-14). Text-mining open-ended survey responses using structural topic modeling: A practical demonstration to understand parents' coping methods during the COVID-19 pandemic in Singapore. Journal of Technology in Human Services 40 (4) : 296-318. ScholarBank@NUS Repository. https://doi.org/10.1080/15228835.2022.2036301
Source Title:	Journal of Technology in Human Services
URI:	https://scholarbank.nus.edu.sg/handle/10635/236394
ISSN:	1522-8835
DOI:	10.1080/15228835.2022.2036301
Appears in Collections:	Elements Staff Publications

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