EMINDS:理解用户行为的进展,在社交媒体上探索心理健康
IEEE transactions on visualization and computer graphics
|November 12, 2025
概括
这项研究介绍了EMINDS,这是一种用于分析在线心理健康社区 (OMHC) 数据的视觉分析系统. EMINDS有助于识别行为阶段及其对心理健康的长期影响,帮助早期干预策略.
科学领域:
- 计算机科学 计算机科学
- 心理健康研究 心理健康研究
- 人与计算机的交互
背景情况:
- 心理健康是一个关键的社会问题.
- 在线心理健康社区 (OMHC) 为行为分析提供了丰富的数据.
- 目前的序列挖掘方法缺乏追踪行为进展和长期心理健康影响的能力.
研究的目的:
- 开发EMINDS,一种用于分析OMHC用户行为的视觉分析系统.
- 要提取不同的行为阶段,并评估它们对心理健康的影响随着时间的推移.
- 为理解行为模式及其演变提供交互式可视化.
主要方法:
- 开发了一种新的自动采矿管道,以识别行为阶段.
- 集成交互式可视化,包括以模式为中心的桑基图.
- 分析了来自Reddit的用户行为,以评估系统的有效性.
主要成果:
- EMINDS成功地提取了不同的行为阶段及其时间演变.
- 该系统揭示了影响长期心理健康的用户行为模式.
- 案例研究和专家采访验证了该系统的有效性和可用性.
结论:
- EMINDS提供了一种强大的工具,用于理解OMHCs中复杂的用户行为.
- 该系统有助于识别与心理健康轨迹相关的行为模式.
- EMINDS支持社会科学家开发数据驱动的心理健康早期干预策略.
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