What makes an opinion leader: Expertise vs popularity
研究社会网络中个体如何通过加权同伴信念来学习，发现受欢迎度（特征向量中心性）和专业度（信息精度）共同决定社会影响力，甚至完全无知的个体也能促进社会学习，但给极受欢迎者提供更好信息可能分散对专家的关注，导致社会评估更差。
This paper studies learning through social networks in which agents update their beliefs by weighting those of their peers. We allow agents to pay little attention to peers with poor information at first, but more later on, as that peer acquires better information from more knowledgeable agents. We derive explicitly how social influence depends on agents' popularity (eigenvector centrality) and expertise (information precision) and show that even completely uninformed agents can contribute to social learning. In certain cases, providing better information to extremely popular agents may distract attention from the views of the experts, and lead society to worse assessments.