一个因果测试的弱联系的强度
Karthik Rajkumar1, Guillaume Saint-Jacques1, Iavor Bojinov2
1LinkedIn Corporation, 700 E Middlefield Rd, Mountain View, CA 94043, USA.
Science (New York, N.Y.)
|September 15, 2022
概括
在LinkedIn上,弱势关系可以促进就业流动性, 但这种影响是非线性的, 温和的关系往往会产生最好的结果.
科学领域:
- 社会网络分析
- 劳动经济学
- 社会学
背景情况:
- "弱势关系的强度"理论认为,较弱的社会联系可以促进人们获得新的机会.
- 了解像LinkedIn这样的专业网络中的弱点关系对于职业流动至关重要.
- 之前的研究主要依赖于观察数据,缺乏因果证据.
研究的目的:
- 通过实验研究弱联系对LinkedIn专业网络中的就业流动性的因果关系.
- 在大规模的数字环境中测试弱链理论的细微差别.
- 找出缓解劳动力强度与就业流动性之间的关系的因素.
主要方法:
- 分析了大规模的随机实验,
- 在用户网络中操纵弱链的普遍性.
- 追踪新的联系方式和职位转换.
主要成果:
- 实验证据证实,弱势关系增加了就业流动性,支持弱势关系理论的实力.
- 观察到一个反向的U型关系:弱势关系增加了就业流动性,随后的回报率下降.
- 较弱的联系对就业流动的影响各不相同:中等弱的联系 (通过相互联系) 和最弱的联系 (通过互动强度) 对就业流动的影响最大.
- 发现了行业差异:在数字化行业中较弱的联系更有效,而在数字化程度较低的行业中较强的联系更有利.
结论:
- 弱势关系的强度是不线性的,并表现出边际回报的减少.
- 联系强度 (互动强度与相互联系) 的定义和测量对工作流动性产生重大影响.
- 在促进就业流动方面,弱或强联系的有效性取决于环境,因行业数字化而有所不同.
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