CMU-S3D-25-103
Software and Societal Systems Department
School of Computer Science, Carnegie Mellon University



CMU-S3D-25-103

Matthew Hicks

May 2025

Ph.D. Thesis
Societal Computing

CMU-S3D-25-103.pdf
Currently Unavailable


Keywords: Social-cyber security, social network analysis, BEND framework, large language models, synthetic social media

As social media platforms have become central to information dissemination, influence operations, and narrative shaping, understanding their role within the broader information environment is increasingly vital. The BEND framework offers a structure for analyzing online influence by identifying social-cyber maneuvers.

The BEND framework was previously operationalized at the message and individual levels. In this thesis, I operationalize the BEND framework at the population and effects levels, integrate both sets of work, and align them with U.S. military doctrine and training. In doing so, I identify the critical need for complex, realistic, and scalable social media training environments.

To meet this need, I introduce the AI-Enabled Scenario Orchestration and Planning (AESOP) tool, which enables planners to create training scenarios that specify events, actors, social media platform accounts, and narratives. AESOP generates synthetic templates associated with the scenario and accompanying news articles, media content, and URLs.

I then present SynTel and SynX, agent-based simulation and generation tools. These tools consume AESOP-generated synthetic templates and, with support from external large language models, produce realistic and interactive synthetic social media data for X/Twitter and Telegram. These simulations replicate influence ecosystems at scale.

Finally, I propose and validate a novel effects-based approach to detecting BEND maneuvers within topic-oriented groups. This technique is applied to real-world datasets to link maneuver effects to broader campaign impacts.

Together, these contributions enhance our capacity to detect, evaluate, and train against influence operations – making BEND a practical analysis framework for the information environment.

282 pages

Thesis Committee:
Kathleen M. Carley (Chair)
Patrick S. Park
Mohamed Farag
David M. Beskow (United States Military Academy)

Nicolas Christin, Head, Software and Societal Systems Department
Martial Hebert, Dean, School of Computer Science


Return to: SCS Technical Report Collection
School of Computer Science

This page maintained by reports@cs.cmu.edu