How social influence affects the wisdom of crowds in influence networks
Ye Tian, Long Wang, Francesco Bullo

TL;DR
This paper provides a rigorous theoretical analysis of how social influence affects the collective wisdom of groups, showing that the impact depends on social power distribution and individual susceptibilities.
Contribution
It introduces a formal mathematical model of opinion dynamics in influence networks and identifies conditions under which social influence improves or undermines collective wisdom.
Findings
Social power allocation determines whether influence improves or undermines wisdom.
More accurate individuals should be less susceptible and have higher network centrality to enhance wisdom.
In democratic networks, the susceptibility of accurate individuals critically affects collective accuracy.
Abstract
A long-standing debate is whether social influence improves the collective wisdom of a crowd or undermines it. This paper addresses this question based on a naive learning setting in influence systems theory: in our models individuals evolve their estimates of an unknown truth according to the weighted-average opinion dynamics. A formal mathematization is provided with rigorous theoretical analysis. We obtain various conditions for improving, optimizing and undermining the crowd accuracy, respectively. We prove that if the wisdom of finite-size group is improved, then the collective estimate converges to the truth as group size increases, provided individuals' variances are finite. We show that whether social influence improves or undermines the wisdom is determined by the social power allocation of the influence system: if the influence system allocates relatively larger social power…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Complex Network Analysis Techniques · Social Capital and Networks
