Title

Understanding Peer Endorsements among gig workers

Abstract

User-generated content (UGC) is an important feature of the Internet, affecting the behavior of individuals or organizations on digital platforms. It is important for platform owners to understand the factors that motivate users to produce UGC. This study focuses on endorsements, a category of UGC that acts as a complementary mechanism to determine the quality/integrity of the skills of a given worker. We first apply social value orientation theory to categorize worker behavior based on their endorsement activity. Using data from a large freelancer platform, we propose to investigate the attributes of the worker which influence the generation of endorsements.

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