How to select crowdsourcing teams with limited information? A heterogeneous information network embedding approach

Yuanyuan Lai (), Min Li (), Junjun Liu () and Huimin Liu ()
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Yuanyuan Lai: Nanjing University
Min Li: Nanjing University
Junjun Liu: Nanjing University
Huimin Liu: Nanjing University

Electronic Commerce Research, 2025, vol. 25, issue 3, No 4, 1423-1451

Abstract: Abstract Crowdsourcing has become a widely accepted approach to leverage crowds to solve business problems, and how to find proper solvers has been widely discussed. Existing studies mainly focus on matching tasks and individuals for simple tasks. However, the increasing complexity of projects calls for the crowdsourcing team selection, whereas the difficulty lies in the limited background information of team members which leads to data sparsity and cold-start problems. Motivated by this problem, we develop CT-HIN, a heterogeneous information network embedding method to evaluate skill matching and communication by similarity searching based on the pair-wise random walk model from multi-dimension. An empirical evaluation with input data collected from a real-world crowdsourcing platform is conducted to justify our proposed approach.

Keywords: Crowdsourcing; Heterogeneous information network; Project team selection (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10660-023-09744-y

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