主题建模和社交网络分析方法来探索印度的Twitter上的糖尿病话语
Thilagavathi Ramamoorthy1, Vaitheeswaran Kulothungan2,3, Bagavandas Mappillairaju4
1School of Public Health, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India.
Frontiers in artificial intelligence
|February 27, 2024
概括
社交媒体,特别是推特,是印度糖尿病管理和意识的宝贵工具. 这项研究确定了关键的讨论主题和有影响力的卫生专业人员和组织分享重要信息.
科学领域:
- 公共卫生 公共卫生
- 数字健康数字健康
- 社交媒体分析
背景情况:
- 社交媒体平台为公共卫生话语提供了一个动态的空间,特别是对于糖尿病等慢性疾病.
- 了解在线对话对于定制糖尿病预防和管理策略至关重要.
- 印度的Twitter景观为健康沟通和干预提供了重要机会.
研究的目的:
- 为了比较在印度推特上分析糖尿病相关讨论的主题建模技术.
- 识别印度糖尿病Twitter社区中普遍存在的主题,信息来源和有影响力的用户.
主要方法:
- 使用Twitter API收集了来自印度的Twitter数据 (2022年11月 - 2023年2月).
- 应用和比较无监督机器学习主题模型:潜伏迪里克莱特分配 (LDA),非负矩阵因子化 (NMF),BERTopic和Top2Vec.
- 进行社交网络分析以确定有影响力的用户.
主要成果:
- 非负矩阵因子化 (NMF) 和BERTopic模型表现出卓越的性能.
- 与糖尿病相关的八个核心主题出现了:促进,管理,药物/个人故事,后果,风险因素/研究,意识/支持,饮食和意见/生活方式的变化.
- 主要影响者包括卫生专业人员和医疗保健组织.
结论:
- 社交媒体分析,特别是主题建模,可以有效地识别与糖尿病相关的关键主题和有影响力的声音.
- 卫生专业人员和组织对于在线传播糖尿病信息至关重要.
- 医疗保健利益相关者和政府之间的合作努力可以提高公众意识和预防非传染性疾病.
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