以 Reddit 使用者生成內容探討糖尿病照護社會支持

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：107

、訪客IP：3.137.189.14

姓名

洪宗銘(Tsung-Ming Hung) 查詢紙本館藏

畢業系所

資訊管理學系

論文名稱

以 Reddit 使用者生成內容探討糖尿病照護社會支持
(Social Support for Diabetes Care on Reddit: A User-Generated Content Approach)

相關論文

★ 以機器學習技術為基礎建構新生兒孕育健康狀態預測模型	★ 電子病歷縮寫消歧與一對多分類任務
★ 使用文字探勘與深度學習技術建置中風後肺炎之預測模型	★ 精準社群廣告投資策略：以機器學習技術為基礎之社會影響力管理模式
★ 智慧活躍老化之實現：以資料驅動為基礎之AI長者在地交友推薦模式	★ 整合深度學習技術與SOR理論之資訊情緒傳遞性探索：新聞生成特質與資訊情感傳播行為
★ 基於混合過濾的電影推薦系統	★ 防範於未然：基於機器學習技術之網路入侵偵測系統
★ 可靠度驗證實驗室導入人工智慧技術的可行性探討 -以A公司為例	★ 智慧共同照護之實現: 以資料驅動為基礎之 AI 糖尿病個案管理模式
★ Non-Touch Cooperation: An Interactive Mechanism Design Based on Mid-Air Gestures	★ 基於 UGC 的反脆弱社交口碑策略:以臺灣飯店業為例
★ 基於機器學習技術之誘導式評論過濾機制：以餐廳評論為例	★ 資料驅動的球隊經營：NBA球隊競爭力與抱團策略之研究

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2028-6-29以後開放)

摘要(中)

隨著全球糖尿病盛行率的持續增長以及社群媒體在慢性疾病管理中的重要性日益凸顯，理解糖尿病相關的線上社群支持行為模式變得至關重要。本研究聚焦於 Reddit 糖尿病社群，對使用者在該社群中尋求與提供支持的行為模式進行深入探討。通過分析 466 則貼文和 2,546 條回覆，並應用詞嵌入技術與深度學習分類模型，對貼文中的支持尋求策略和回覆中的社會支持類型進行了自動化分類。結果顯示，社群成員在尋求支持時主要採取「尋求支持」策略，而在提供支持時以「資訊性支持」為主。同時，研究也發現，不同尋求策略會對應到不同的社會支持類別，如「慶祝成就」的策略大多獲得「尊重支持」。這些發現對於糖尿病護者及其醫療保健人員提供了寶貴的行為指引，有助於提供更精準的支持與指導。使外，在模型方面，貼文分類模型的準確率達到了 90%，而回覆分類模型的準確率達 72%。這些結果為社群研究者和資料科學家在自動化分類支持尋求策略和社會支持類別提供了有效的參數及方法。

摘要(英)

As the global prevalence of diabetes continues to rise and the significance of social media in the management of chronic diseases increasingly stands out, it has become critical to understand the online community support behavior patterns associated with diabetes. This study focuses on the Reddit diabetes community, exploring in-depth the behavioral patterns of users seeking and providing support within this community. Through analyzing 466 posts and 2,546 comments, and applying word embedding techniques and deep learning classification models, the study automatically classifies support seeking strategies in posts and types of social support in comments. Results indicate that when community members seek support, they mainly adopt the "Seeking support" strategy, whereas "Informational support" is primarily provided. Furthermore, it was discovered that different seeking strategies correspond to different categories of social support, such as the "Celebrating achievements" strategy mostly receiving "Esteem support". These findings provide valuable behavioral guidance for diabetes caregivers and their healthcare professionals, aiding in delivering more precise support and guidance. Regarding the models, the post classification model achieved an accuracy of 90%, while the comment classification model reached an accuracy of 72%. These results offer effective parameters and methods for community researchers and data scientists in automatically classifying support-seeking strategies and social support categories.

關鍵字(中)

★ 糖尿病
★ 社群媒體
★ 社會支持
★ Reddit
★ 詞嵌入
★ 深度學習

關鍵字(英)

★ Diabetes
★ social media
★ social support
★ Reddit
★ word embedding
★ deep learning

論文目次

摘要 .............................................................................................................................................i Abstract.......................................................................................................................................ii Acknowledgements ...................................................................................................................iii Table of Contents.......................................................................................................................iv List of Figures............................................................................................................................vi List of Tables ...........................................................................................................................viii I. Introduction ............................................................................................................................. 1
1-1 Research Background and Motivation ......................................................................... 1 1-2 Research Objectives ..................................................................................................... 6 1-3 Research Structure........................................................................................................7
II. Literature Review.................................................................................................................10 2-1 Diabetes Mellitus........................................................................................................10 2-2 Social Media...............................................................................................................12 2-3 Social Support ............................................................................................................ 13 2-4 Seeking-Support Strategy...........................................................................................18
III. Methodology.......................................................................................................................20 3-1 Framework .................................................................................................................20 3-2 Data Collection...........................................................................................................23
iv
3-3 Data Preprocessing.....................................................................................................30 3-4 Feature Engineering ...................................................................................................32 3-5 Classification Modeling .............................................................................................34 3-6 Evaluation Metrics .....................................................................................................36
IV. Research Results and Discussion........................................................................................37 4-1 Analysis of Support-Seeking Strategies in Posts........................................................ 37 4-2 Analysis of Social Support Types in Comments ........................................................ 44 4-3 Support-Seeking Strategies and Social Support Types ..............................................48 4-4 Analysis of Classification Model Results...................................................................51
V. Research Conclusion and Contribution................................................................................58 5-1 Conclusion and Contribution .....................................................................................58 5-2 Limitation and Future Research ................................................................................. 61
Reference .................................................................................................................................. 62

參考文獻

American Diabetes, A. (2004). Gestational Diabetes Mellitus. Diabetes care, 27, S88-90. https://doi.org/https://doi.org/10.2337/diacare.27.2007.S88
Attai, D. J., Cowher, M. S., Al-Hamadani, M., Schoger, J. M., Staley, A. C., & Landercasper, J. (2015). Twitter Social Media is an Effective Tool for Breast Cancer Patient Education and Support: Patient-Reported Outcomes by Survey. Journal of Medical Internet Research, 17(7), e188. https://doi.org/10.2196/jmir.4721
Baker, B., & Yang, I. (2018). Social media as social support in pregnancy and the postpartum. Sex Reprod Healthc, 17, 31-34. https://doi.org/10.1016/j.srhc.2018.05.003
Brownson, C. A., & Heisler, M. (2009). The Role of Peer Support in Diabetes Care and Self-Management. The Patient: Patient-Centered Outcomes Research, 2(1), 5-17. https://doi.org/10.2165/01312067-200902010-00002
Buehler, E. M., Crowley, J. L., Peterson, A. M., & High, A. C. (2019). Broadcasting for help: A typology of support-seeking strategies on Facebook. New Media & Society, 21(11-12), 2566-2588. https://doi.org/10.1177/1461444819853821
Burleson, B. R., MacGeorge, E. L., Knapp, M., & Daly, J. (2002). Supportive communication. Handbook of interpersonal communication, 3, 374-424.
Care, D. (2019). Care in Diabetesd2019. Diabetes care, 42(1), S13-S28.
Centers for Disease Control and Prevention. (2022). National Diabetes Statistics Report. https://www.cdc.gov/diabetes/data/statistics-report/diagnosed-undiagnosed-diabetes.html
Centers for Disease Control and Prevention. (2023). Basics about diabetes. https://www.cdc.gov/diabetes/basics/diabetes.html
Chen, L. (2019). A Classification Framework for Online Social Support Using Deep Learning. HCI in Business, Government and Organizations. Information Systems and Analytics, Cham.
Chulis, K. (2016). Data mining Twitter for cancer, diabetes, and asthma insights Purdue University.
Cutrona, C. E., & Suhr, J. A. (1992). Controllability of Stressful Events and Satisfaction With Spouse Support Behaviors. Communication Research, 19(2), 154-174. https://doi.org/10.1177/009365092019002002
De Choudhury, M., & Kıcıman, E. (2017). The Language of Social Support in Social Media and its Effect on Suicidal Ideation Risk. Proceedings of the International AAAI Conference on Weblogs and Social Media, 2017, 32-41.
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv:1810.04805. https://ui.adsabs.harvard.edu/abs/2018arXiv181004805D
Federation, I. D. (2021). IDF Diabetes Atlas, 10th edn. https://www.diabetesatlas.org
Gabarron, E., Dorronzoro, E., Rivera-Romero, O., & Wynn, R. (2019). Diabetes on Twitter: A Sentiment Analysis. Journal of Diabetes Science and Technology, 13(3), 439-444. https://doi.org/10.1177/1932296818811679
Harandi, T. F., Taghinasab, M. M., & Nayeri, T. D. (2017). The correlation of social support with mental health: A meta-analysis. Electron Physician, 9(9), 5212-5222. https://doi.org/10.19082/5212
Haslam, D. M., Tee, A., & Baker, S. (2017). The Use of Social Media as a Mechanism of Social Support in Parents. Journal of Child and Family Studies, 26(7), 2026-2037. https://doi.org/10.1007/s10826-017-0716-6
Kahanovitz, L., Sluss, P. M., & Russell, S. J. (2017). Type 1 Diabetes - A Clinical Perspective. Point Care, 16(1), 37-40. https://doi.org/10.1097/poc.0000000000000125
Kamel Boulos, M. N., & Wheeler, S. (2007). The emerging Web 2.0 social software: an enabling suite of sociable technologies in health and health care education. Health Information & Libraries Journal, 24(1), 2-23. https://doi.org/10.1111/j.1471-1842.2007.00701.x
Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59-68. https://doi.org/10.1016/j.bushor.2009.09.003
Kaplan, B. H., Cassel, J. C., & Gore, S. (1977). Social support and health. Med Care, 15(5 suppl), 47-58. https://doi.org/10.1097/00005650-197705001-00006
Katsarou, A., Gudbjörnsdottir, S., Rawshani, A., Dabelea, D., Bonifacio, E., Anderson, B. J., Jacobsen, L. M., Schatz, D. A., & Lernmark, Å. (2017). Type 1 diabetes mellitus. Nature Reviews Disease Primers, 3(1), 17016. https://doi.org/10.1038/nrdp.2017.16
Kim, H. (2014). Enacted Social Support on Social Media and Subjective Well-being. International journal of communication, 8. https://ijoc.org/index.php/ijoc/article/view/2243
Lett, H. S., Blumenthal, J. A., Babyak, M. A., Strauman, T. J., Robins, C., & Sherwood, A. (2005). Social Support and Coronary Heart Disease: Epidemiologic Evidence and Implications for Treatment. Psychosomatic Medicine, 67(6). https://journals.lww.com/psychosomaticmedicine/Fulltext/2005/11000/Social_Support_and_Coronary_Heart_Disease_.7.aspx
Levengood, T. W., Peng, Y., Xiong, K. Z., Song, Z., Elder, R., Ali, M. K., Chin, M. H., Allweiss, P., Hunter, C. M., & Becenti, A. (2019). Team-Based Care to Improve Diabetes Management: A Community Guide Meta-analysis. American Journal of Preventive Medicine, 57(1), e17-e26. https://doi.org/10.1016/j.amepre.2019.02.005
Liu, Y., Mei, Q., Hanauer, D. A., Zheng, K., & Lee, J. M. (2016). Use of Social Media in the Diabetes Community: An Exploratory Analysis of Diabetes-Related Tweets. JMIR Diabetes, 1(2), e4. https://doi.org/10.2196/diabetes.6256
Longo, D. R., Schubert, S. L., Wright, B. A., LeMaster, J., Williams, C. D., & Clore, J. N. (2010). Health information seeking, receipt, and use in diabetes self-management. Annals of Family Medicine, 8(4), 334-340. https://doi.org/10.1370/afm.1115
Maness, J. M. (2006). Library 2.0 Theory: Web 2.0 and Its Implications for Libraries. Webology, 3.
McCall, A. L., & Farhy, L. S. (2013). Treating type 1 diabetes: from strategies for insulin delivery to dual hormonal control. Minerva Endocrinol, 38(2), 145-163.
McIntyre, H. D., Catalano, P., Zhang, C., Desoye, G., Mathiesen, E. R., & Damm, P. (2019). Gestational diabetes mellitus. Nature Reviews Disease Primers, 5(1), 47. https://doi.org/10.1038/s41572-019-0098-8
Ogurtsova, K., da Rocha Fernandes, J. D., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., Cavan, D., Shaw, J. E., & Makaroff, L. E. (2017). IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Research and Clinical Practice, 128, 40-50. https://doi.org/https://doi.org/10.1016/j.diabres.2017.03.024
Papatheodorou, K., Banach, M., Bekiari, E., Rizzo, M., & Edmonds, M. (2018). Complications of Diabetes 2017. Journal of Diabetes Research, 2018, 3086167. https://doi.org/10.1155/2018/3086167
Patel, K. D., Zainab, K., Heppner, A., Srivastava, G., & Mago, V. (2020). Using Twitter for diabetes community analysis. Network Modeling Analysis in Health Informatics and Bioinformatics, 9(1), 36. https://doi.org/10.1007/s13721-020-00241-y
Paterson, B. L., Thorne, S., & Dewis, M. (1998). Adapting to and managing diabetes. Journal of Nursing Scholarship, 30(1), 57-62. https://doi.org/10.1111/j.1547-5069.1998.tb01237.x
Pew Research Center, W., D.C. (2015). Social Media Usage: 2005-2015. https://www.pewresearch.org/internet/2015/10/08/social-networking-usage-2005-2015/
Plows, J. F., Stanley, J. L., Baker, P. N., Reynolds, C. M., & Vickers, M. H. (2018). The Pathophysiology of Gestational Diabetes Mellitus. International Journal of Molecular Sciences, 19(11), 3342. https://www.mdpi.com/1422-0067/19/11/3342
Prati, G., & Pietrantoni, L. (2010). The relation of perceived and received social support to mental health among first responders: a meta-analytic review [https://doi.org/10.1002/jcop.20371]. Journal of Community Psychology, 38(3), 403-417. https://doi.org/https://doi.org/10.1002/jcop.20371
Rad, G. S., Bakht, L. A., Feizi, A., & Mohebi, S. (2013). Importance of social support in diabetes care. Journal of Education and Health Promotion, 2, 62. https://doi.org/10.4103/2277-9531.120864
Raffel, L. J., & Goodarzi, M. O. (2014). Diabetes Mellitus. In Reference Module in Biomedical Sciences. Elsevier. https://doi.org/10.1016/B978-0-12-801238-3.05558-6
Rui, J. R., Chen, Y., & Damiano, A. (2013). Health organizations providing and seeking social support: a Twitter-based content analysis. Cyberpsychol Behav Soc Netw, 16(9), 669-673. https://doi.org/10.1089/cyber.2012.0350
Saha, A., & Agarwal, N. (2015). Demonstrating Social Support from Autism Bloggers Community on Twitter Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015, Paris, France. https://doi.org/10.1145/2808797.2809364
Selkie, E., Adkins, V., Masters, E., Bajpai, A., & Shumer, D. (2020). Transgender Adolescents′ Uses of Social Media for Social Support. Journal of Adolescent Health, 66(3), 275-280. https://doi.org/10.1016/j.jadohealth.2019.08.011
Shaw, R. J., & Johnson, C. M. (2011). Health Information Seeking and Social Media Use on the Internet among People with Diabetes. Journal of Public Health Informatics, 3(1), ojphi.v3i1.3561. https://doi.org/10.5210/ojphi.v3i1.3561
Simmons, K. M., & Michels, A. W. (2015). Type 1 diabetes: A predictable disease. World Journal of Diabetes, 6(3), 380-390. https://doi.org/10.4239/wjd.v6.i3.380
Sun, H., Saeedi, P., Karuranga, S., Pinkepank, M., Ogurtsova, K., Duncan, B. B., Stein, C., Basit, A., Chan, J. C. N., Mbanya, J. C., Pavkov, M. E., Ramachandaran, A., Wild, S. H., James, S., Herman, W. H., Zhang, P., Bommer, C., Kuo, S., Boyko, E. J., & Magliano, D. J. (2022). IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Research and Clinical Practice, 183, 109119. https://doi.org/https://doi.org/10.1016/j.diabres.2021.109119
van Dam, H. A., van der Horst, F. G., Knoops, L., Ryckman, R. M., Crebolder, H. F. J. M., & van den Borne, B. H. W. (2005). Social support in diabetes: a systematic review of controlled intervention studies. Patient Education and Counseling, 59(1), 1-12. https://doi.org/https://doi.org/10.1016/j.pec.2004.11.001
Walker, K. Z., O’Dea, K., Gomez, M., Girgis, S., & Colagiuri, R. (2010). Diet and exercise in the prevention of diabetes. Journal of Human Nutrition and Dietetics, 23(4), 344-352. https://doi.org/10.1111/j.1365-277X.2010.01061.x
Wilson, E. V., Wang, W., & Sheetz, S. D. (2014). Underpinning a Guiding Theory of Patient-Centered E-Health. Communications of the Association for Information Systems, 34, 16. https://doi.org/10.17705/1CAIS.03416
Wongkoblap, A., Vadillo, M. A., & Curcin, V. (2017). Researching Mental Health Disorders in the Era of Social Media: Systematic Review. Journal of Medical Internet Research, 19(6), e228. https://doi.org/10.2196/jmir.7215
World Health Organization. (2023). Diabetes. https://www.who.int/news-room/fact-sheets/detail/diabetes
Xuemei, Y., & Lan, L. (2016, 23-25 Aug. 2016). Researches on marital quality, well-being and social support of IT employees 2016 11th International Conference on Computer Science & Education (ICCSE), Nagoya, Japan. https://doi.org/10.1109/ICCSE.2016.7581579

指導教授

曾筱珽(Hsiao-Ting Tseng)

審核日期

2023-6-29

推文