在线癌症论坛中挖掘公共讨论的文本分析方法:分析多意向肺癌治疗数据集的分析
Adnan Muhammad Shah1, Kang Yoon Lee2, Abdullah Hidayat3
1Chair of Marketing and Innovation, University of Hamburg, 20146, Germany; Department of Physics, Charles E. Schmidt College of Science, Florida Atlantic University, FL 33431-0991, United States; Department of Computer Engineering, Gachon University, Seoul 13120. Republic of Korea.
在线癌症论坛揭示了肺癌讨论的季节性趋势. 治疗护理主题在春季达到顶峰,而息护理讨论在夏末上升,突出了公共沟通动态.
科学领域:
- 计算语言学计算语言学
- 公共卫生沟通公共卫生沟通
- 瘤病人的社区.
背景情况:
- 在线癌症论坛 (OCF) 对于患者和护理人员的信息交换至关重要.
- 这些平台生成大量的非结构化文本数据,需要进行分析.
- 了解在线讨论提供了对患者需求和经验的见解.
研究的目的:
- 将主题建模应用于在线癌症论坛数据.
- 确定肺癌治疗中的关键讨论主题.
- 分析在线话语的时间和季节性变化.
主要方法:
- 从三个OCF (2016-2018) 收集了27,998个肺癌论坛帖子.
- 利用时间序列分析和主题建模.
- 检查了不同肺癌治疗意图的讨论动态.
主要成果:
- 癌症症状和预防是治疗和息护理中占主导地位的主题.
- 治疗护理的讨论在冬季到春晚达到顶峰;缓和护理在夏末到秋中达到顶峰.
- 对于查,治疗和瘤控制主题,注意到季节性变化.
结论:
- 对OCFs的计算文本分析为癌症传播趋势提供了宝贵的见解.
- 识别季节性变化有助于理解公共话语.
- 研究结果支持改善个性化护理,决策支持和生活质量.
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