Nonverbal Peer Feedback and User Contribution in Online Forums: Experimental Evidence of the Role of Attribution and Emotions

Ramesh Shankar, Lei Wang, Kunter Gunasti, Hongfei Li

Research output: Contribution to journalArticlepeer-review

Abstract

Peer feedback is often associated with an increase in the contributions of members in online communities. Verbal feedback (such as a review) can give details about how the recipient can improve their contribution, but it requires the recipient to read and process the feedback. Conversely, nonverbal feedback (such as an upvote) is easy to comprehend but does not convey much helpful information. Prior studies have mainly focused on the impact of verbal feedback. However, little has been done to explore the underlying mechanism of the effect of nonverbal peer feedback on people’s tendency to contribute more. We present two experimental studies conducted on Amazon Mechanic Turk. Study 1 demonstrates how verbal and nonverbal feedback impact user contributions differently. Next, building on attribution-emotion-action theory, we use Study 2 to establish a causal mechanism between nonverbal feedback and users’ knowledge contribution. Specifically, users who receive nonverbal peer feedback make internal and external attributions, which in turn impact their emotions and contribution decisions. We find that users receiving more positive feedback attribute this in equal measure internally to perceived self-efficacy and externally to perceived fairness, whereas users who receive negative feedback attribute it more to the lack of perceived fairness of peer feedback. These findings have important implications for both content-sharing platforms and researchers trying to better understand the drivers of online content-sharing behavior.

Original languageEnglish (US)
Article number7
Pages (from-to)267-303
Number of pages37
JournalJournal of the Association for Information Systems
Volume25
Issue number2
DOIs
StatePublished - 2024

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications

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