About

Sorin Adam Matei is a Professor of Communication at the Brian Lamb School of Communication at Purdue University, with a primary research focus on human-technology interaction. His interests include information theory applied to digital knowledge creation, innovation, data storytelling, trust, and command and control. He studies the relationship between information technology, group behavior, and social structures in various contexts, including national defense and security, modeling and simulating communication and information processes in collaboration and conflict, and the evolution of online groups. His notable work includes the book 'Structural Differentiation in Social Media,' which analyzed ten years of Wikipedia editing to offer insights into how online groups emerge and evolve, emphasizing the role of strong, temporary leaders for online project success. He has published extensively in reputable journals and his research has been funded by the National Science Foundation, often in collaboration with colleagues from computer science and engineering.

Research topics

• Computer Science
• Sociology
• Artificial Intelligence
• Political Science
• Psychology
• Communication
• Epistemology
• Art
• Social psychology
• Advertising
• Cartography
• Data science
• World Wide Web
• Public relations
• Business
• Remote sensing
• Geology
• Geography
• Literature
• Media studies
• Philosophy

Selected publications

• Risk-Prone and Risk-Averse Behavior in Natural Emergencies: An Appraisal Theory Approach

  ArXiv.org · 2025-03-27

  preprintOpen access1st authorCorresponding

  Individuals who shared actionable information during Hurricane Sandy were significantly more likely to exhibit risk-prone behavior, as measured by a novel Risk Behavior Quotient (RBQ). Using a dataset of 36595 geo-located tweets from 774 users in the New York area, we found that a higher proportion of actional tweets predicted increased exposure to physical even if overall users ultimately moved toward lower-risk zones. This counterintuitive finding suggests that proactivity, manifested in sharing crisis relevant content, correlates with greater exposure to risk, possibly due to increased mobility or engagement in hazardous areas. In contrast, a greater number of social media peers was associated with reduced risk exposure. This study builds on appraisal theory, which frames risk-related decisions as outcomes of cognitively mediated emotional and rational evaluations. We extend this theory to digital crisis behavior, distinguishing between emotional and actional appraisals expressed via social media. Tweets were categorized using sentiment analysis and semantic classification, enabling the isolation of affective and behavioral signals. Our methodology combines natural language processing with spatial vector analysis to estimate individual movement paths and risk exposure based on evacuation and flooding maps. The resulting RBQ captures both direction and intensity of risk behavior, allowing us to model how online communication reflects and predicts real-world risk engagement during natural disasters.

  PublisherOA PDFDOI

• Disinformation as Ground-Shifting in Great-Power Competition

  The US Army War College Quarterly Parameters · 2025-09-16

  articleOpen access1st authorCorresponding

  Disinformation, distinct from misinformation, replaces accepted principles of objectivity and verifiability with novelty, framing, authority, self-reference, and conformity to create a new “truth paradigm.” This article introduces a novel definition and framework for understanding disinformation as a strategic tool in great-power competition. It includes a review of case studies, such as Russian disinformation campaigns during the Russia-Ukraine War and analyzes cognitive biases and social behaviors that facilitate the spread of disinformation. Policy and military practitioners will find actionable insights into countering disinformation, including its sociopsychological mechanisms and proposed targeted counterstrategies to protect the integrity of information flows in defense and security contexts.

  PublisherOA PDFDOI

• Risk-Prone and Risk-Averse Behavior in Natural Emergencies: An Appraisal Theory Approach

  2025-04-07

  preprintOpen access1st authorCorresponding

  Individuals who shared actionable information during Hurricane Sandy were significantly more likely to exhibit risk-prone behavior, as measured by a novel Risk Behavior Quotient (RBQ). Using a dataset of 36,595 geo-located tweets from 774 users in the New York area, we found that a higher proportion of actional tweets predicted increased exposure to physical even if overall users ultimately moved toward lower-risk zones. This counterintuitive finding suggests that proactivity—manifested in sharing crisis-relevant content—correlates with greater exposure to risk, possibly due to increased mobility or engagement in hazardous areas. In contrast, a greater number of social media peers was associated with reduced risk exposure.This study builds on appraisal theory, which frames risk-related decisions as outcomes of cognitively mediated emotional and rational evaluations. We extend this theory to digital crisis behavior, distinguishing between emotional and actional appraisals expressed via social media. Tweets were categorized using sentiment analysis and semantic classification, enabling the isolation of affective and behavioral signals.Our methodology combines natural language processing with spatial vector analysis to estimate individual movement paths and risk exposure based on evacuation and flooding maps. The resulting RBQ captures both direction and intensity of risk behavior, allowing us to model how online communication reflects and predicts real-world risk engagement during natural disasters.

  PublisherOA PDFDOI

• Mission Command’s Asymmetric Advantage Through AI-Driven Data Management

  The US Army War College Quarterly Parameters · 2025-12-17

  articleOpen access1st authorCorresponding

  Artificial intelligence can optimize mission command by condensing multisource field data that ascends the decision chain while distilling concise, decision-quality guidance to the tactical edge. Diverging from existing publications, this article positions information asymmetry as a defining pillar of mission command rather than a limitation. This article presents a condensation-distillation framework that manages complexity through data condensation, AI-driven distillation, and conceptual metrics to assess asymmetric information flows. Drawing on military doctrine, algorithmic-warfare literature, and current modernization programs, military practitioners will engage with a systems-thinking perspective, revealing how AI-enabled command and control can enhance decision clarity and reinforce the intent of mission command.

  PublisherOA PDFDOI

• Quantum computers are like kaleidoscopes − why unusual metaphors help illustrate science and technology

  2024-06-14

  articleOpen access1st authorCorresponding
  PublisherDOI

• Legal and Ethical Dimensions in Addressing Human Rights in the Design and Implementation of Artificial Intelligence

  Frontiers of artificial intelligence, ethics and multidisciplinary applications. · 2024-01-01

  book-chapterSenior author
  PublisherDOI

• Ethical reasoning in artificial intelligence: A cybersecurity perspective

  The Information Society · 2024-11-27 · 5 citations

  article1st authorCorresponding
  PublisherDOI

• What Should a Strategist Know and Do, and Why

  Military Strategy Magazine · 2023-05-11

  articleSenior author

  We propose a realist theory definition of military strategy from which we derive a set of competencies and a matrix for their use in the strategic process. The article describes how competencies work when they intersect with the strategic process. A strategic thinking and matrix identifies negotiation and systems thinking as the most important competencies.

  PublisherDOI

• Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a focus group report

  arXiv (Cornell University) · 2023-11-02 · 1 citations

  preprintOpen access

  The emergence of AI tools in cybersecurity creates many opportunities and uncertainties. A focus group with advanced graduate students in cybersecurity revealed the potential depth and breadth of the challenges and opportunities. The salient issues are access to open source or free tools, documentation, curricular diversity, and clear articulation of ethical principles for AI cybersecurity education. Confronting the "black box" mentality in AI cybersecurity work is also of the greatest importance, doubled by deeper and prior education in foundational AI work. Systems thinking and effective communication were considered relevant areas of educational improvement. Future AI educators and practitioners need to address these issues by implementing rigorous technical training curricula, clear documentation, and frameworks for ethically monitoring AI combined with critical and system's thinking and communication skills.

  PublisherOA PDFDOI

• ETHICS-2023 Session B1 - Panel: Perspectives from Liberal Arts on the practical turn in AI Ethics

  2023-05-18

  articleOpen access

  The increasing proliferation of advanced digital technologies like artificial intelligence (AI) capable of performing tasks and making decisions previously reserved for humans has surfaced important ethical questions. Emerging transformative applications like generative and multi-modal AI systems and automated decision-support systems in government have raised the stakes as developers, regulators, researchers, and civil society have worked to respond. Current discourse emphasizes issues like the distribution of costs and benefits across groups and contexts, the translation of principle-based frameworks to practices, the role of diversity and public participation, and trade-offs between goals like innovation and the protection of human rights. Yet dominant responses in scholarly and policy discourse have emphasized some perspectives and solutions while other approaches have arguably not been fully explored.

  PublisherOA PDFDOI

Recent grants

• KredibleNet - Building a research community and proposing a research agenda for the study and modeling of reputation and authority across informal knowledge markets

  NSF · $180k · 2013–2014

Frequent coauthors

• Amy Van Epps

  Cabot (United States)

  50 shared

• Michael Thomas Smith

  50 shared

• Jeffrey J. Evans

  University of California, Davis

  50 shared

• García Esteban

  Universidad de Alcalá

  49 shared

• Elisa Bertino

  Purdue University System

  16 shared

• Brian Britt

  University of Alabama

  16 shared

• Sandra J. Ball‐Rokeach

  University of Southern California

  13 shared

• Robert Bruno

  8 shared

Education

• Ph.D., Computer Science

  University of California, Berkeley

  2005

• M.S., Computer Science

  University of California, Berkeley

  2001

• B.S., Computer Science

  University of Bucharest

  1998

Awards & honors

• several award-winning