The Impact of Gratitude-Embedded Messages on Online Pro-Social Behaviors
56 Pages Posted: 23 Nov 2015 Last revised: 19 Nov 2016
Date Written: November 15, 2016
Using detailed social broadcasting data from an online charitable giving campaign on Twitter, we evaluate two competing models of economic incentives on online pro-social behavior. Specifically, we focus on the effectiveness of gratitude-embedded messages on online charitable giving behavior, conditional on the distance the message travels over social networks. We use two novel methods in text mining – topic modeling and personality extraction techniques – to operationalize message content and user heterogeneity, and employ a two-stage message reception-donation model for parameter estimation. We find that gratitude-embedded messages produce more favorable results than donation-matching messages. While the effect of both gratitude-embedded messages as well as donation-matching messages dissipate over network distance, we find that the effect of gratitude-embedded messages decays more slowly and that gratitude has more resilience over longer network distances compared to monetary incentives such as donation-matching.
Keywords: Social Networks, Gratitude, Prosocial Behaviors, Charitable Giving, Topic Modeling, Twitter
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