Kathleen M. Carley

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

Selected publications

• Social cybersecurity: an emerging science

  Computational and Mathematical Organization Theory · 2020 · 143 citations

  1st authorCorresponding

  With the rise of online platforms where individuals could gather and spread information came the rise of online cybercrimes aimed at taking advantage of not just single individuals but collectives. In response, researchers and practitioners began trying to understand this digital playground and the way in which individuals who were socially and digitally embedded could be manipulated. What is emerging is a new scientific and engineering discipline-social cybersecurity. This paper defines this em…

  DOI

• Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines

  Journal of Computational Social Science · 2020 · 96 citations

  Senior authorCorresponding
  DOI

• A survey of social cybersecurity: Techniques for attack detection, evaluations, challenges, and future prospects

  Computers in Human Behavior Reports · 2025-04-15 · 9 citations

  articleOpen access

  In today’s age of digital interconnectedness, understanding and addressing the nuances of social cybersecurity have become paramount. Unlike its broader counterparts, information security and cybersecurity, which are focused on safeguarding all forms of sensitive data and digital systems, social cybersecurity places its emphasis on the human and social dimensions of cyber threats. This field is uniquely positioned to address issues such as different social cybersecurity attacks like cyberbullyin…

  PublisherDOI

• 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…

  PublisherOA PDFDOI

• 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 categ…

  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

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)

Similar researchers at Carnegie Mellon University

• Norman Sadehh-63
• James Herbslebh-58
• Cleotilde (Coty) Gonzalezh-47