Contextual centrality: going beyond network structure.

ABSTRACT: Centrality is a fundamental network property that ranks nodes by their structural importance. However, the network structure alone may not predict successful diffusion in many applications, such as viral marketing and political campaigns. We propose contextual centrality, which integrates structural positions, the diffusion process, and, most importantly, relevant node characteristics. It nicely generalizes and relates to standard centrality measures. We test the effectiveness of contextual centrality in predicting the eventual outcomes in the adoption of microfinance and weather insurance. Our empirical analysis shows that the contextual centrality of first-informed individuals has higher predictive power than that of other standard centrality measures. Further simulations show that when

SUBMITTER: Leng Y 

PROVIDER: S-EPMC7286920 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature