Understanding telemedicine service users’ perceptions: A text mining analysis on social media discussion
| dc.contributor.author | Shang, Yanyan | |
| dc.contributor.author | Kim, J.B. (Joo Baek) | |
| dc.contributor.author | Shin, Soo Il | |
| dc.date.accessioned | 2022-12-27T19:08:12Z | |
| dc.date.available | 2022-12-27T19:08:12Z | |
| dc.date.issued | 2023-01-03 | |
| dc.description.abstract | Telemedicine has drawn noticeable attention due to the advancement of information technology, and it saw a surge in popularity during the COVID-19 pandemic. This study is aimed at understanding telemedicine users’ perceptions on their care services, as well as identifying the aspects of telemedicine that can be improved to enhance users’ experience and satisfaction. Specifically, we utilized a topic modeling approach with Latent Dirichlet Allocation (LDA) to analyze telemedicine-related discussion posts on Reddit to discover the topics and themes that telemedicine service users are interested in, as well as the perceptions that users have of those topics and themes. 11 topics and 6 themes were discovered by the LDA algorithm. Lastly, we provide our suggestions and insights on how telemedicine services and practitioners can implement the themes, as well as directions for future study. | |
| dc.format.extent | 9 | |
| dc.identifier.doi | https://doi.org/10.24251/HICSS.2023.413 | |
| dc.identifier.isbn | 978-0-9981331-6-4 | |
| dc.identifier.other | a548d1c2-119d-4022-87be-f1535fe7d67c | |
| dc.identifier.uri | https://hdl.handle.net/10125/103044 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Proceedings of the 56th Hawaii International Conference on System Sciences | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Social Media and Healthcare Technology | |
| dc.subject | lda | |
| dc.subject | social media | |
| dc.subject | telemedicine | |
| dc.subject | text mining | |
| dc.subject | topic modeling | |
| dc.title | Understanding telemedicine service users’ perceptions: A text mining analysis on social media discussion | |
| dc.type.dcmi | text | |
| prism.startingpage | 3358 |
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