Network theory-based interventions could be particularly effective for promoting technology adoption when information friction serves as the major obstacle to technology diffusion. To inform policy makers interested in such interventions, this paper systematically reviews empirical evidence on determinants of how social networks shape technology diffusion. It identifies three sets of factors that individually and jointly affect technological diffusion on social networks: Population characteristics, including those describe overall network structures and key economic agents’ network positions and technology sophistication; technology parameters; and information propagation mechanisms. Accurate social network assessment—crucial for the formulation of network interventions—relies on making careful selection out of the many measures of network characteristics and layers of socioeconomic interactions to examine, and on accurately defining the scope and size of network data to collect. Evidence indicates effective network interventions should aim to introduce new technologies first to economic agents with high centrality or clustering, sufficient resemblance to average population, and whom are incentivized to communicate with others.

中文翻译：

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通过社交网络影响技术传播的因素：经验证据的回顾

当信息摩擦成为技术传播的主要障碍时，基于网络理论的干预可能对促进技术采用特别有效。为了告知对此类干预感兴趣的政策制定者，本文系统地回顾了关于社交网络如何影响技术传播的决定因素的经验证据。它确定了三组单独和共同影响社交网络上技术传播的因素： 人口特征，包括描述整体网络结构和关键经济主体的网络位置和技术成熟度的特征；技术参数；和信息传播机制。准确的社会网络评估——对于制定网络干预措施至关重要——依赖于从众多衡量网络特征和社会经济互动层次的指标中进行仔细选择以进行检查，以及准确定义要收集的网络数据的范围和规模。有证据表明，有效的网络干预应旨在首先将新技术引入具有高中心性或集群性、与普通人口足够相似以及被激励与他人交流的经济主体。