Social meta-inference and the evidentiary value of consensus
Reasoning beyond available data is a ubiquitous feature of human cognition. But while the availability of first-hand data typically diminishes as the concepts we reason about become more complex, our ability to draw inferences seems not to. We may offset the sparsity of direct evidence by observing the statements of others, but such social meta-inference comes with challenges of its own. The strength of socially-provided evidence depends on multiple factors which themselves must be inferred, like the knowledge, social goals, and independence of the people providing the data. Here, we present the results of an experiment aimed at examining how people draw conclusions from information provided by others in the context of social media posts. By systematically varying the degree of consensus along with the number of people and distinct arguments involved we are able to assess how much each factor affects the conclusions reasoners draw. Across a range of topics we find that while people are influenced by the number of people on each side of an argument, the number of posts is the dominant factor driving belief revision. In contrast to well established findings in simpler domains, we find that people are largely insensitive to the diversity of the arguments made.