传统的社会学习预测了网络偏差? 在社会学习理论中探索冒犯的多功能性论文
You Zhou1, Weidi Liu2, Claire Lee3
1School of Social Science, Monash University, Melbourne, VIC, Australia.
Behavioral sciences & the law
|May 20, 2024
概括
社会学习理论通过冒犯多功能性和规范性来解释网络偏差. 在线学习介绍了传统的学习.
科学领域:
- 犯罪学 犯罪学
- 网络心理学 网络心理学
- 社会学习理论社会学习理论
背景情况:
- 社会学习理论 (SLT) 对于理解网络偏差至关重要.
- 现有的研究主要集中在攻击规范上,忽视了攻击的多功能性.
- 这种差距限制了对在线犯罪社会学习模式的全面理解.
研究的目的:
- 调查网络偏差中违反多功能性和规范性的共存.
- 检查在线社会学习在网络偏差中的调解作用.
- 为了比较传统社会学习对网络支持与网络依赖犯罪的预测能力.
主要方法:
- 在3741名中国大学生样本上利用二进制后勤回归.
- 分析了四种类型的网络犯罪:性骚扰,网络欺凌,黑客攻击和数字盗版.
- 对比了传统和在线社会学习变量的影响.
主要成果:
- 在网络偏差中,冒犯多功能性和规范性并存,规范性解释了稍微更多的差异.
- 在线学习变量调解了传统学习和网络偏差之间的关系.
- 传统的社会学习比网络依赖犯罪更强烈地预测了网络犯罪.
结论:
- 经验证据支持网络偏差中冒犯多功能性和规范性之间的非排他性关联.
- 在线社会学习发挥着重要的调解作用.
- 了解传统和在线学习对于预防和干预网络偏差至关重要.
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