本文采用社会网络分析方法对以埃博拉病毒为主题的公共健康话语网络进行了研究。发现两个网络呈现了稠密与稀疏的相对差异。相比于#CDCCHAT，#EBOLA表现了较为离散的结构，较为稀疏的关系，较弱的双向对话性，以及较低的集群化程度。此外，本研究在对“意见领袖”经典文献的梳理基础上，尝试从关系结构角度界定本文的 “关键影响者”及其测量纬度。进而在两个网络中确认了18个“关键影响者”并分析了她们的结构，身份特征，及其在双向对话中的作用。最后讨论了本研究的发现之于我国本土健康传播的实践意义。

This study adopted social network analysis (SNA) to examine health conversations on Ebola virus on Twitter. The author mapped the two networks and the clusters within, and discovered structural differences between sparsely-knit and densely-knit structures. Compared with #CDCCHAT, #EBOLA shows relatively discrete structures, sparse connections, less reciprocal dialogue, and lower clustering degree. Additionally, based upon literature review on classic studies on “opinion leaders”, the author attempted to operationalize the “key in?uencers” with a structural approach. 18 such key in?uencers were identifed and their structural and personal features were explored. The study also discussed the role of in?uencers in the promotion of twoway dialogue. Potential values of this study on Chinese health communication practice were discussed.