在线寻找亲密关系:对成功预测因素的机器学习分析
Germano Vera Cruz1, Elias Aboujaoude2, Lucien Rochat3
1Department of Psychology, University of Picardie Jules Verne, Amiens, France.
Cyberpsychology, behavior and social networking
|June 23, 2023
概括
用户对Tinder (STU) 和离线约会 (STOD) 的满意度受年龄和动机的影响. 使用约会应用程序来应对情绪与不满有关,这表明它们不是有效的应对机制.
科学领域:
- 心理学 心理学 心理学
- 社会学 社会学 社会学
- 人与计算机的交互
背景情况:
- 关于在线约会服务存在广泛的研究,但有限的研究集中在用户对约会应用程序的满意度和随后的离线互动上.
- 约会应用程序已成为形成关系的普遍工具,需要了解用户体验和满意度水平.
研究的目的:
- 评估成年用户对Tinder使用 (STU) 和Tinder离线约会 (STOD) 的满意度.
- 从28个变量列表中确定STU和STOD的关键预测因素.
主要方法:
- 使用机器学习模型分析了1387名Tinder用户的数据,这些用户填写了在线问卷.
- 满意度的预测因素根据机器学习模型的重要性排名.
主要成果:
- 平均STU为2.39 (4点级) 和平均STOD为3.05 (5点级).
- 参与者的年龄和使用Tinder的动机 (例如,增强,情绪应对,社交,找到真爱,随意性) 是满意度的强有力的预测因素.
- 与精神病理学相关的变量与满意度有负相关性.
- 很大一部分用户 (65.3%) 已婚或处于恋爱关系中,50.3%的用户打算在线约会.
结论:
- 约会应用程序的满意度受到用户人口统计和动机的重大影响.
- 使用约会应用程序作为情绪应对机制与更高的不满症有关,这表明它们是一种无效的应对策略.
- 这些发现强调需要解决潜在的心理问题,这些问题可能会推动约会应用程序的使用,特别是为了应对目的.
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