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Preprints, Working Papers, ... Year : 2021

Social Capital Accumulation Through Social Media Networks


Work-related social media networks (SMNs) like LinkedIn introduce novel networking opportunities and features that promise to help individuals establish, extend, and maintain social capital (SC). Typically, work-related SMNs offer access to advanced networking features only to premium users in order to encourage basic users to become paying members. Yet, little is known about whether access to these advanced networking features has a causal impact on the accumulation of SC. To close this research gap, we conducted a randomized field experiment and recruited 215 freelancers on a freemium, work-related SMN. Out of these recruited participants, more than 70 received a randomly assigned, free, 12-month premium membership voucher. We observe that individuals do not necessarily accumulate more SC from the ability to access advanced networking features, as the treated freelancers did not automatically change their digitized networking engagement. Those features will only unfold their full utility if the individuals are motivated to proactively engage in networking: Freelancers who have access to advanced networking features increase their SC by 4.609% for each unit increase on the strategic networking behavior scale. We confirm this finding in another study utilizing a second, individual-level panel data covering 52,392 freelancers; in tandem, we investigate the dynamics that active vs. passive features play in SC accumulation. Based on the findings, we introduce the “theory of purposeful feature utilization”: essentially, individuals must not only possess an efficacious “networking weapon"––they also need the intent to “shoot” it.
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Dates and versions

hal-03501727 , version 1 (23-12-2021)


  • HAL Id : hal-03501727 , version 1


Michael Weiler, Simon Stolz, Andreas Lanz, Christian Schlereth, Oliver Hinz. Social Capital Accumulation Through Social Media Networks: Evidence from a Randomized Field Experiment and Individual-Level Panel Data. 2021. ⟨hal-03501727⟩


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