(Mis)alignment between facial and textual emotions and its effects on donors engagement behavior in online crowdsourcing platforms

Elham Yazdani (), Anindita Chakravarty () and Jeff Inman ()
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Elham Yazdani: Terry College of Business, University of Georgia
Anindita Chakravarty: Terry College of Business, University of Georgia
Jeff Inman: University of Pittsburgh

Journal of the Academy of Marketing Science, 2025, vol. 53, issue 4, No 2, 968-988

Abstract: Abstract Although textual and facial emotion expressions in prosocial appeals have been studied separately in past research, there has been little work on the misalignment (compared to alignment) between them. Using a multi-method approach comprising experiments and panel data of 6,098 crowdfunding projects from Gofundme, we investigate how emotions expressed in the cover image and the project description interact to increase potential donors’ engagement as measured by metrics relevant to the platform, i.e., donation amount per donor. More specifically, we focus on the misalignment (vs. alignment) between happy and sad facial expressions in images and the positive and negative emotions in the project description. Our empirical analysis shows that misalignment scenarios have a bigger positive impact on the donor’s contributed amount, compared to alignment scenarios. We also show that such a relative impact is heterogeneous and differs based on expressed urgency, beneficiary age, and progress towards donation goal. We make a theoretical contribution via assessing the extent of cognitive processing in misalignment vs alignment cases. We propose situations with a tradeoff such that the extent of cognitive processing of multimodal information content can be reduced due to simultaneous activation of affective processing. Our research provides strategic recommendations for platforms to increase donors’ engagement and platform revenue management.

Keywords: Crowdfunding; Donor engagement; Emotional misalignment; Facial emotions; Textual emotions; Perceived cognition; Endogeneity; Multi-method research (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11747-024-01002-3

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