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.