Airoldi Edoardo M, Christakis Nicholas A
Department of Statistics, Operations, and Data Science, Fox School of Business, Temple University, Philadelphia, PA 19122, USA.
Data Science Institute, Temple University, Philadelphia, PA 19122, USA.
Science. 2024 May 3;384(6695):eadi5147. doi: 10.1126/science.adi5147.
Certain people occupy topological positions within social networks that enhance their effectiveness at inducing spillovers. We mapped face-to-face networks among 24,702 people in 176 isolated villages in Honduras and randomly assigned villages to targeting methods, varying the fraction of households receiving a 22-month health education package and the method by which households were chosen (randomly versus using the friendship-nomination algorithm). We assessed 117 diverse knowledge, attitude, and practice outcomes. Friendship-nomination targeting reduced the number of households needed to attain specified levels of village-wide uptake. Knowledge spread more readily than behavior, and spillovers extended to two degrees of separation. Outcomes that were intrinsically easier to adopt also manifested greater spillovers. Network targeting using friendship nomination effectively promotes population-wide improvements in welfare through social contagion.
某些人在社交网络中占据着拓扑位置，这增强了他们引发传播效应的能力。我们绘制了洪都拉斯176个与世隔绝村庄中24702人的面对面社交网络，并将村庄随机分配至不同的干预方法，改变接受为期22个月健康教育套餐的家庭比例以及选择家庭的方法（随机选择与使用友谊提名算法）。我们评估了117种不同的知识、态度和行为结果。基于友谊提名的干预方法减少了达到全村特定接受水平所需的家庭数量。知识的传播比行为更容易，且传播效应延伸至两个分隔度。本质上更容易采用的结果也表现出更大的传播效应。使用友谊提名的社交网络干预方法通过社会传播有效地促进了全人群的福利改善。
