About

Dr. Kathleen M. Carley's research integrates cognitive science, sociology, organization science, and computer science to tackle complex social and organizational challenges. She is renowned for establishing Dynamic Network Analysis (DNA), a theory and methodology designed to examine large, high-dimensional, time-variant networks. Her work on DNA has led to the creation of tools that analyze large-scale dynamic networks and various multi-agent simulation systems. Dr. Carley has spearheaded the development of tools for extracting sentiment, social and semantic networks, and cues from textual data, including AutoMap and NetMapper, as well as simulating epidemiological models with BioWar and simulating changes in beliefs and practices through information campaigns with Construct. Her ORA system is recognized as a premier network analysis and visualization technology used globally, supporting reasoning about geospatial and dynamic high-dimensional network data, with capabilities for handling both small and big data, social media data, and network dynamics. Her illustrative projects encompass assessment of disinformation and social cyber-security threats, IRS outreach, the impact of NextGen on airline re-routing, counter-terrorism and counter-narcotics modeling, health analytics, social media analytics of elections, and crisis analysis including Benghazi, Darfur, the Arab Spring, and COVID-19.

Research topics

• Computer Science
• Sociology
• Political Science
• Computer Security
• Artificial Intelligence
• Internet privacy
• Psychology
• Data science
• Engineering ethics
• Applied psychology
• Social psychology
• Law
• Developmental psychology
• Engineering
• World Wide Web
• Public relations
• Marketing
• Gender studies

Selected publications

• Cyber Attack Flow Intelligence Network: Backbone Analysis and Defense Strategy Optimization

  IEEE Transactions on Network Science and Engineering · 2026-01-01

  articleSenior author

  Cyberattacks increasingly unfold as multi-stage campaigns, creating a practical challenge for defenders with limited budgets: where to place controls to disrupt adversary pathways most effectively. To address this question, we construct a Cyber Attack Flow Intelligence Network using 1,031 technical and analytical reports mapped to 170 MITRE ATT&CK groups and 50 campaigns. Using this dataset, we first apply backbone analysis to identify the core patterns of attack progression and the cross-domain transition patterns. We then compute the minimum multi-vertex cut to determine the smallest optimal set of blocking techniques that can interrupt the paths leading from commonly observed initial-access techniques to high-impact objectives such as ransomware, data destruction, and financial theft. We also interpret the cost of blocking a specific technique as a defensive cost and formulate defense planning as a budget-constrained interdiction problem. Our analysis shows that when security budgets are sufficient, the most effective strategy is to build technically robust defenses that disrupt post-intrusion activity. When budgets are limited, reducing human-driven vulnerabilities through employee security training and preventing initial malware execution becomes the most effective approach. These findings provide a data-driven basis for prioritizing security investments.

  PublisherDOI

• The Dual Personas of Social Media Bots

  2026-04-16 · 1 citations

  book-chapterOpen accessSenior author

  Social media bots are Artificial Intelligent (AI) agents that participate in online conversations. Most studies focus on the general bot and the malicious nature of these agents. However, bots have many different personas, each specialized toward a specific behavioral or content trait. Neither are bots singularly bad, because they are used for both good and bad information dissemination. In this chapter, we introduce fifteen agent personas of social media bots. These personas have two main categories: Content-Based Bot Persona and Behavior-Based Bot Persona. We also form yardsticks of the good-bad duality of the bots, elaborating on metrics of good and bad bot agents. Our work puts forth a guideline to inform bot detection regulation, emphasizing that policies should focus on how these agents are employed, rather than collectively terming bot agents as bad.

  PublisherOA PDFDOI

• 66. Examining Adolescent Social Networks and Dental Utilization in the National Longitudinal AddHealth Study

  Journal of Adolescent Health · 2026-02-13

  article
  PublisherDOI

• A Baseline Simulation of Hybrid Misinformation and Spearphishing Campaigns in Organizational Networks

  2025-12-07

  articleSenior author
  PublisherDOI

• Promoting Social Corrections: A Media Literacy Intervention for Misinformation on Social Media

  Lecture notes in computer science · 2025-10-08

  book-chapterSenior author
  PublisherDOI

• Are LLM-Powered Social Media Bots Realistic?

  Lecture notes in computer science · 2025-10-08 · 1 citations

  book-chapterSenior author
  PublisherDOI

• Extending the BEND Framework to Webgraphs

  Lecture notes in computer science · 2025-10-08

  book-chapterSenior author
  PublisherDOI

• Emotions moderate the influence of moral values on attitude stability

  Computational and Mathematical Organization Theory · 2025-09-26 · 1 citations

  articleOpen accessSenior author

  Abstract Moral values and emotions interact to shape attitudes and their strength. While prior research suggests that attitudes associated with moral judgments are more resistant to change, this relationship has primarily been examined using self-reported measures. Moreover, emotions are closely tied to moral judgments, yet their moderating role in the morality-attitude stability relationship remains under explored. Using over 15 million tweets about COVID-19 vaccines from 1.7 million users over a year on X (formerly Twitter), we examine the interaction between moral and emotional associations and stability of attitudes towards COVID-19 vaccines over time. Our findings reveal that emotions shape the effects of moral values in nuanced ways– all emotions except disgust amplify the positive impact of care on stability, sadness diminishes the destabilizing effects of purity and liberty, and happiness does not influence the role of authority or fairness. These findings highlight the complex interplay between morality and emotions in shaping attitude persistence, contributing to a deeper understanding of moralized attitudes in digital discourse. The study also underscores the value of social media as a tool for investigating attitude dynamics beyond traditional self-report measures.

  PublisherOA PDFDOI

• Bridging Social Media and Search Engines: Dredge Words and the Detection of Unreliable Domains

  Proceedings of the International AAAI Conference on Web and Social Media · 2025-06-07

  articleOpen accessSenior author

  Proactive content moderation requires platforms to rapidly and continuously evaluate the credibility of websites. Leveraging the direct and indirect paths users follow to unreliable websites, we develop a website credibility classification and discovery system that integrates both webgraph and large-scale social media contexts. We additionally introduce the concept of dredge words—terms or phrases for which unreliable domains rank highly on search engines—and provide the first exploration of their usage on social media. Our graph neural networks that combine webgraph and social media contexts generate to state-of-the-art results in website credibility classification and significantly improves the top-k identification of unreliable domains. Additionally, we release a novel dataset of dredge words, highlighting their strong connections to both social media and online commerce platforms.

  PublisherOA PDFDOI

• Limited effectiveness of psychological inoculation against misinformation in a social media feed

  PNAS Nexus · 2025-05-28 · 3 citations

  articleOpen access

  Psychological inoculation is a promising and potentially scalable approach to counter misinformation. The goal of inoculation is to teach people to recognize manipulation techniques, such as emotional language, commonly found in misinformation online. While there is substantial evidence that inoculation increases technique recognition when directly assessed, it is not clear if this effect transfers to spontaneous detection of techniques and disengagement with the associated content in real-life contexts. In particular, emotional appeals are abundant on social media and known drivers of attention and engagement. Therefore, we examined the effects of emotional language and emotional manipulation inoculation on attention and engagement in a simulated social media feed environment. Through five preregistered studies, we found that inoculation only decreased engagement with emotionally presented content when we solely presented synthetic content relevant to the task of identifying emotional manipulation. Any addition of real tweets or even synthetic tweets containing other manipulation techniques (e.g. ad hominem attacks) into the feed appeared to nullify the effect. Our results highlight the importance of assessing misinformation interventions in ecologically valid contexts to estimate real-world effects.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01LM009516

  NIH · $1.7M · 2012

• Measuring Network Stability and Fit

  NIH · $1.3M · 2013–2018

• ITR: Modeling Distributed Denial of Service Attacks and Defenses

  NSF · $819k · 2002–2007

• IGERT Formal Proposal: Multidisciplinary Training Program in Computational Analysis of Social and Organizational Systems

  NSF · $2.5M · 1999–2009

Frequent coauthors

• C. T. M. Kwok

  64 shared

• Michael Wooldridge

  64 shared

• Nigel Gilbert

  University of Surrey

  64 shared

• Michael N. Huhns

  University of South Carolina

  64 shared

• Nicholas R. Jennings

  Loughborough University

  64 shared

• Yves Demazeau

  Laboratoire d'Informatique de Grenoble

  64 shared

• Katia Sycara

  64 shared

• Lynnette Hui Xian Ng

  51 shared

Labs

• CASOS CenterPI

  The Center for Computational Analysis of Social and Organizational Systems

Education

• Ph.D.

  Harvard

• Other

  University of Zurich

Awards & honors

• National Academies Monographs: A Decadal Survey of the Socia…
• From Maps to Models: Augmenting the Nation's Geospatial Inte…
• Developing a 21st Century Global Library for Mathematics Res…
• Frontiers in Massive Data Analysis (2013)
• Future U.S. Workforce for Geospatial Intelligence (2013)