Combining advanced computational social science and graph theoretic techniques to reveal adversarial information operations

Mustafa Alassad, Billy Spann, Nitin Agarwal

Abstract: Highlights•Integrating traditional centrality and spectral modularity methods to explore intensive focal structures in social networks.•Applying decomposition optimization method to maximize the individual centrality measure and the network modularity value in the network level in complex social networks.•Measuring the influence generated by each focal structure on the individual level and the network level.•Applying the DCFM to measure the power generated by each focal structure.•Applying Newman-Girvan modularity method and depth-first search and linear graph algorithm to validate our results.•Evaluating model performance- apply to different social and real-world networks.•Implementing a toy example as a complexity analysis, and a real-world Twitter network.•Applying different centrality methods (degree, betweenness, closeness, eigenvector) and compare their results.