Do Online Voting Patterns Reflect Evolved Features of Human Cognition? An Exploratory Empirical Investigation

Priestley, Maria; Mesoudi, Alex

Abstract

Online votes or ratings can assist internet users in evaluating the credibility and appeal of the information which they encounter. For example, aggregator websites such as Reddit allow users to up-vote submitted content to make it more prominent, and down-vote content to make it less prominent. Here we argue that decisions over what to up- or down-vote may be guided by evolved features of human cognition. We predict that internet users should be more likely to up-vote content that others have also up-voted (social influence), content that has been submitted by particularly liked or respected users (model-based bias), content that constitutes evolutionarily salient or relevant information (content bias), and content that follows group norms and, in particular, prosocial norms. 489 respondents from the online social voting community Reddit rated the extent to which they felt different traits influenced their voting. Statistical analyses confirmed that norm-following and prosociality, as well as various content biases such as emotional content and originality, were rated as important motivators of voting. Social influence had a smaller effect than expected, while attitudes towards the submitter had little effect. This exploratory empirical investigation suggests that online voting communities can provide an important test-bed for evolutionary theories of human social information use, and that evolved features of human cognition may guide online behaviour just as it guides behaviour in the offline world.

Citation

Priestley, M., & Mesoudi, A. (2015). Do Online Voting Patterns Reflect Evolved Features of Human Cognition? An Exploratory Empirical Investigation. PLoS ONE, 10(6), Article e0129703. https://doi.org/10.1371/journal.pone.0129703

• Journal Article Type: Article
• Acceptance Date: May 12, 2015
• Online Publication Date: Jun 11, 2015
• Publication Date: Jun 11, 2015
• Deposit Date: May 16, 2018
• Publicly Available Date: May 16, 2018
• Journal: PLoS ONE
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 6
• Article Number: e0129703
• DOI: https://doi.org/10.1371/journal.pone.0129703