Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media Data
Objectives This study examined the symptoms and emotions expressed by older adults with cancer and their caregivers in South Korean online cancer communities. It aimed to identify narrative patterns and provide insights to inform personalized care strategies. Methods We analyzed 6,908 user-generated...
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| Format: | Article |
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The Korean Society of Medical Informatics
2025-04-01
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| Series: | Healthcare Informatics Research |
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| Online Access: | http://e-hir.org/upload/pdf/hir-2025-31-2-175.pdf |
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| author | Kyunghwa Lee Soomin Hong |
| author_facet | Kyunghwa Lee Soomin Hong |
| author_sort | Kyunghwa Lee |
| collection | DOAJ |
| description | Objectives This study examined the symptoms and emotions expressed by older adults with cancer and their caregivers in South Korean online cancer communities. It aimed to identify narrative patterns and provide insights to inform personalized care strategies. Methods We analyzed 6,908 user-generated posts collected from major online cancer communities in South Korea. Keyword frequency analysis, term frequency-inverse document frequency, 2-gram analysis, and latent Dirichlet allocation-based topic modeling were applied to explore language patterns. Sentiment analysis identified 12 emotional categories, and Pearson correlation coefficients were calculated to examine associations between symptoms and emotional expressions. All data were cleaned and standardized prior to analysis. Results Many users expressed anxiety (20.63%) and depression (19.59%), frequently associated with chemotherapy and sleep disturbances. Among reported symptoms, sleep problems carried the highest negative sentiment (79.81%), underscoring their profound impact on well-being. Topic modeling consistently revealed seven recurring themes, including treatment decision-making, symptom management, and concerns about family, demonstrating the layered and personalized experiences of older cancer patients and their caregivers. Conclusions This study explored treatment-related and symptom-related difficulties faced by older adults with cancer. Many reported significant emotional strain, especially anxiety, depression, and sleep disturbances. These findings highlight the necessity for supportive strategies addressing both psychological and physical aspects of care. Future research could investigate the utility of large language models in analyzing these narratives, provided the data is ethically managed and appropriate for such use. |
| format | Article |
| id | doaj-art-dec2ee8bb8a249edb1588da736e07513 |
| institution | OA Journals |
| issn | 2093-3681 2093-369X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | The Korean Society of Medical Informatics |
| record_format | Article |
| series | Healthcare Informatics Research |
| spelling | doaj-art-dec2ee8bb8a249edb1588da736e075132025-08-20T01:52:14ZengThe Korean Society of Medical InformaticsHealthcare Informatics Research2093-36812093-369X2025-04-0131217518810.4258/hir.2025.31.2.1751249Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media DataKyunghwa Lee0Soomin Hong1 College of Nursing, Konyang University, Daejeon, Korea Red Cross College of Nursing, Chung-Ang University, Seoul, KoreaObjectives This study examined the symptoms and emotions expressed by older adults with cancer and their caregivers in South Korean online cancer communities. It aimed to identify narrative patterns and provide insights to inform personalized care strategies. Methods We analyzed 6,908 user-generated posts collected from major online cancer communities in South Korea. Keyword frequency analysis, term frequency-inverse document frequency, 2-gram analysis, and latent Dirichlet allocation-based topic modeling were applied to explore language patterns. Sentiment analysis identified 12 emotional categories, and Pearson correlation coefficients were calculated to examine associations between symptoms and emotional expressions. All data were cleaned and standardized prior to analysis. Results Many users expressed anxiety (20.63%) and depression (19.59%), frequently associated with chemotherapy and sleep disturbances. Among reported symptoms, sleep problems carried the highest negative sentiment (79.81%), underscoring their profound impact on well-being. Topic modeling consistently revealed seven recurring themes, including treatment decision-making, symptom management, and concerns about family, demonstrating the layered and personalized experiences of older cancer patients and their caregivers. Conclusions This study explored treatment-related and symptom-related difficulties faced by older adults with cancer. Many reported significant emotional strain, especially anxiety, depression, and sleep disturbances. These findings highlight the necessity for supportive strategies addressing both psychological and physical aspects of care. Future research could investigate the utility of large language models in analyzing these narratives, provided the data is ethically managed and appropriate for such use.http://e-hir.org/upload/pdf/hir-2025-31-2-175.pdfnatural language processingneoplasmsagedsigns and symptomscaregivers |
| spellingShingle | Kyunghwa Lee Soomin Hong Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media Data Healthcare Informatics Research natural language processing neoplasms aged signs and symptoms caregivers |
| title | Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media Data |
| title_full | Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media Data |
| title_fullStr | Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media Data |
| title_full_unstemmed | Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media Data |
| title_short | Symptom and Sentiment Analysis of Older People with Cancer and Caregivers: A Text Mining Approach Using Korean Social Media Data |
| title_sort | symptom and sentiment analysis of older people with cancer and caregivers a text mining approach using korean social media data |
| topic | natural language processing neoplasms aged signs and symptoms caregivers |
| url | http://e-hir.org/upload/pdf/hir-2025-31-2-175.pdf |
| work_keys_str_mv | AT kyunghwalee symptomandsentimentanalysisofolderpeoplewithcancerandcaregiversatextminingapproachusingkoreansocialmediadata AT soominhong symptomandsentimentanalysisofolderpeoplewithcancerandcaregiversatextminingapproachusingkoreansocialmediadata |