Sentence examples for network analytic from inspiring English sources

The third paper in this special issue by Desmarais and Cranmer (Forecasting the locational dynamics of transnational terrorism: a network analytic approach) proposes and evaluates a network analytic approach to predict the geopolitical sources and targets of terrorism.

Our comparative network analytic study of complex systems used data-driven network metrics and their visualizations to explain the relationship dimension of three metropolitan innovation ecosystems.

However, there is little empirical research that addresses the dynamics of media use within a social context using network analytic methods.

We approach the problem of forecasting transnational terrorism from a network analytic perspective with the supposition that the structure of the transnational terrorist network may be the best predictor of its own evolution.

We construct the network of transnational terrorist attacks, in which source (sender) and target (receiver) countries share a directed edge, and we evaluate a network analytic approach to forecasting the geopolitical sources and targets of terrorism.

We examined the consequences of these academy components over time with regard to race by combining ethnographic accounts with social network data collected throughout the academy and using a variety of network analytic tools.

Our analytical approach is evidence-based and data-driven, using network analytics, network metrics, and their visualizations to explain the relationship dimension of innovation ecosystems.

We referred this approach as financial network analytics.

We referred the needed approach as financial network analytics.

Social network analytics methods are being used in the telecommunication industry to predict customer churn with great success.

In this paper, we sketch several research challenges from the above three perspectives of financial network analytics.