数据挖掘创伤:在Reddit上对网络受害者的AI辅助定性研究
J'Andra Antisdel1,2, Wendy R Miller1, Doyle Groves1
1Center for Enhancing Quality of Life in Chronic Illness, School of Nursing, Indiana University Indianapolis, 600 Barnhill Drive, Indianapolis, IN, 46202, United States, 1 574-703-4472.
JMIR infodemiology
|September 3, 2025
概括
这项研究使用数据挖掘来分析Reddit关于网络受害的讨论, 揭示了六个关键主题, 发现突出了人工智能
科学领域:
- 计算社会科学
- 网络心理学
- 数字健康
背景情况:
- 网络攻击带来很大的风险,
- 对于在医疗机构中识别有风险的个人以及了解他们的网络受害者经历,
- 心理和发育因素影响了对网络威胁的易感性和随后的痛苦.
研究的目的:
- 分析用户在社交媒体平台Reddit上描述的网络受害者经历.
- 采用数据挖掘和无需数据的计算分析,
主要方法:
- 使用数据挖掘和文字相邻图 (WAG) 建模的计算定性研究.
- 分析了2012年至2023年的13381条Reddit帖子.
- 通过GPT-4进行后总结和集群标签,严格审查相关性和匿名性.
主要成果:
- 通过WAG建模生成的38个相关集群中确定了35个.
- 六个主要主题出现:心理影响,应对/治愈,在线/离线保护,各种受害者设置,以及寻求理解.
- 与2012-2018年 (5.1%) 相比,2019-2023年的帖子显著增加表明网络受害者讨论正在发展.
结论:
- 数据挖掘和人工智能是对大型公共数据集进行定性分析的有效工具.
- 调查结果可以为未来的网络风险行为和受害者研究提供信息.
- 这些方法可以帮助制定医疗机构网络受害者评估策略.
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