Social network research requires access to realistic graph datasets for testing theories and developing network algorithms. However, available social network data are either small, static or cannot be collected or shared due to privacy issues. Synthetic social network data must capture multi-dimensional network analytical functions and support diverse sets of network applications. To address these challenges, IAI has been awarded a contract entitled, “High Fidelity Synthesis of Dynamic Social Networks using Measurement-based Calibration.” A systematic approach will synthetically generate diverse types of large-scale, dynamic and high fidelity online social network data via dynamic measurement calibration. Scalable algorithms will be designed and implemented along with methods and software tools to generate realistic social network data with respect to multi-dimensional network analytical functions. These will be validated with a comprehensive set of statistical, temporal, and topological metrics, and application-level benchmarks. The key innovation is capturing visible as well as latent or hidden dynamic interactions, patterns and anomalies, information flows and cascades along with the coupled dynamics of network structure and data content like topics, sentiments, and memes, to synthesize social media. This approach does not need input data and can synthesize fully anonymous social network data with target characteristics given as input. By leveraging advanced tools from graph-theoretic, statistical, topological and time-series analysis, this Synthesis of High Fidelity Social Network Data (SHIELD) system will provide an integrated architecture and technology base to support diversity of emerging social media types and to deploy strategic social network applications for high fidelity social network synthesis. This work also facilitates understanding of complex social network behavior and has defense applications in cyberspace including threat detection, deception and counter messaging, as well as several commercial applications.