A causal test of the strength of weak ties

Citations Over TimeTop 1% of 2022 papers

Abstract

The authors analyzed data from multiple large-scale randomized experiments on LinkedIn's People You May Know algorithm, which recommends new connections to LinkedIn members, to test the extent to which weak ties increased job mobility in the world's largest professional social network. The experiments randomly varied the prevalence of weak ties in the networks of over 20 million people over a 5-year period, during which 2 billion new ties and 600,000 new jobs were created. The results provided experimental causal evidence supporting the strength of weak ties and suggested three revisions to the theory. First, the strength of weak ties was nonlinear. Statistical analysis found an inverted U-shaped relationship between tie strength and job transmission such that weaker ties increased job transmission but only to a point, after which there were diminishing marginal returns to tie weakness. Second, weak ties measured by interaction intensity and the number of mutual connections displayed varying effects. Moderately weak ties (measured by mutual connections) and the weakest ties (measured by interaction intensity) created the most job mobility. Third, the strength of weak ties varied by industry. Whereas weak ties increased job mobility in more digital industries, strong ties increased job mobility in less digital industries.

Related Papers

• → Social Networks and Labor Markets: How Strong Ties Relate to Job Finding on Facebook’s Social Network(2016)222 cited
• → The Strength of Weak Ties Revisited: Further Evidence of the Role of Strong Ties in the Provision of Online Social Support(2021)64 cited
• → Labor Market Implications of Weak Ties(2006)10 cited
• → Strong versus weak ties in migration(2018)2 cited
• Weak Ties are Weaker than Strong Ties in Generating Social Capital on Social Networking Sites(2018)