{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:04:11Z","timestamp":1755219851498,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>Palliative care ensures patients\u2019 dignity and quality of life while supporting families during serious illness. However, barriers such as inadequate awareness hinder access to these services. This study analyzed 9,147 perspectives about palliative and hospice care posted on Naver Knowledge iN, a popular online platform in South Korea, using contextualized topic modeling and multi-class sentiment analysis (SA). Nine major themes were identified. SA showed that \u201csadness\u201d was the most common emotion, followed by \u201cneutral\u201d and \u201canxiety.\u201d Notably, negative emotions were closely tied to \u201cemotional and psychological support\u201d theme. The KoBERT model used for SA achieved an accuracy of 0.73 and F1-score of 0.72. These findings highlight the need to address misconceptions and enhance public awareness of palliative care. Recommendations include creating targeted educational resources, implementing proactive screening for emotional distress, and establishing accessible communication platforms.<\/jats:p>","DOI":"10.3233\/shti251059","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:39:37Z","timestamp":1754566777000},"source":"Crossref","is-referenced-by-count":0,"title":["Exploring Public Perceptives on Palliative and Hospice Care in Social Media: Topic Modeling and Multi-Class Sentiment Analysis"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6993-060X","authenticated-orcid":false,"given":"Aeri","family":"Kim","sequence":"first","affiliation":[{"name":"The Research Institute of Nursing Science, Seoul National University, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyungmi","family":"Woo","sequence":"additional","affiliation":[{"name":"College of Nursing, Seoul National University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251059","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:39:38Z","timestamp":1754566778000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251059"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251059","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}