Effects of Attention and Recognition on Engagement, Content Creation and Sharing: Experimental Evidence from an Image Sharing Social Network

Justin T. Huang and Sridhar Narayanan
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Justin T. Huang: U of Michigan
Sridhar Narayanan: Stanford U

Research Papers from Stanford University, Graduate School of Business

Abstract: In this study, we examine the impacts of attention and recognition received by a user's content on a social network on that user's subsequent engagement on the network, content creation and content sharing. The study of the impact of attention and recognition is typically challenging because they are not randomly assigned. Systematic differences within and across users in the degree of attention and recognition received by content shared by them makes the identification of effects difficult. To solve this identification problem, we implemented a field experiment in collaboration with an art-sharing social network, where we experimentally manipulated attention and recognition by selectively featuring users' content. A unique aspect of our experimental context is that we are able to observe both on-network and off-network activity of the individuals concerned. The main results of our experiment are that our manipulation shifting attention and recognition on the network increases engagement, tie-formation, posting of creative output and the usage of underlying software tools used to create content. We explore the temporal variation, heterogeneity, and mediation in these effects.

Date: 2020-12
New Economics Papers: this item is included in nep-exp, nep-pay, nep-soc and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:3919

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