Social Media Information Operations
Tauhid Zaman, Yen-Shao Chen

TL;DR
This paper presents a formal optimization framework for social media influence operations, emphasizing modeling, detection, and countermeasures against misinformation, bots, and influence campaigns in online social networks.
Contribution
It introduces a comprehensive optimization approach for social media influence operations, integrating data-driven tools and discussing the impact of generative AI on offensive and defensive strategies.
Findings
Framework supports targeted opinion shaping
Tools aid in identifying influential users and communities
AI advances enable scalable influence and defenses
Abstract
The battlefield of information warfare has moved to online social networks, where influence campaigns operate at unprecedented speed and scale. As with any strategic domain, success requires understanding the terrain, modeling adversaries, and executing interventions. This tutorial introduces a formal optimization framework for social media information operations (IO), where the objective is to shape opinions through targeted actions. This framework is parameterized by quantities such as network structure, user opinions, and activity levels - all of which must be estimated or inferred from data. We discuss analytic tools that support this process, including centrality measures for identifying influential users, clustering algorithms for detecting community structure, and sentiment analysis for gauging public opinion. These tools either feed directly into the optimization pipeline or…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMisinformation and Its Impacts · Complex Network Analysis Techniques · Spam and Phishing Detection
