Suchergebnisse

This book constitutes the proceedings of the 15th International Conference on Social Computing Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2022, which was held on September 20-23, 2022 in Pittsburgh, Pennsylvania. The goal of this conference is to build a community of social cyber scholars, bringing together and fostering interaction between members of the scientific, corporate, government, and military communities interested in understanding, forecasting, and impacting human sociocultural behavior. It is the charge of this community to build this new science, its theories, methods, and its scientific culture in a way that does not give priority to either social science or computer science, and to embrace change as the cornerstone of the community. As the papers in this volume show, people, theories, methods, and data from a wide number of disciplines are represented including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science. Numerous types of computational methods are used, such as machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics.

Intro -- Preface -- Organization -- Contents -- COVID-Related Focus -- Malicious and Low Credibility URLs on Twitter During the AstraZeneca COVID-19 Vaccine Development -- 1 Introduction -- 2 Data Collection and Processing -- 3 Low Credibility Information Sources -- 4 Malicious URLs -- 5 User Co-sharing Practices -- 6 Conclusions -- References -- How Political is the Spread of COVID-19 in the United States? -- 1 Introduction -- 2 Related Work -- 3 Data Collection -- 3.1 Department of Transportation Data -- 3.2 JHU CSSE COVID-19 Dataset -- 3.3 Other Sources -- 4 Methodology -- 4.1 K-Means Clustering -- 4.2 Calculating Infection Rate -- 4.3 Correlation Analysis -- 5 Analysis Results -- 5.1 Clustering US States -- 5.2 Correlation Analysis -- 5.3 Further Analysis for Travel Patterns After States' Reopening Dates -- 6 Conclusions and Future Work -- References -- Applying an Epidemiological Model to Evaluate the Propagation of Misinformation and Legitimate COVID-19-Related Information on Twitter -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Analysis and Results -- 5 Conclusions and Future Work -- References -- Optimization of Mitigation Strategies During Epidemics Using Offline Reinforcement Learning -- 1 Introduction -- 2 Background -- 2.1 SIR-Based Model for Epidemic Simulation -- 2.2 Markov Decision Process -- 3 Methodology -- 3.1 Extended Model for Epidemic Simulation (SI2R) -- 3.2 Reinforcement Learning for Optimization of Regulations -- 3.3 Offline Reinforcement Learning -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Results -- 5 Conclusion -- References -- Mining Online Social Media to Drive Psychologically Valid Agent Models of Regional Covid-19 Mask Wearing -- Abstract -- 1 Introduction -- 2 Data -- 2.1 Mask-Wearing Data -- 2.2 CMU CASOS/IDeaS COVID-19 Twitter Data.

Detecting Malign Influence -- Misogyny, Women in Power, and Patterns of Social Media Harassment -- Stereotype Content Dictionary: A Semantic Space of 3 Million Words and Phrases Using Google News Word2Vec Embeddings -- Social Cybersecurity Analysis of the Telegram Information Environment During the 2022 Invasion of Ukraine -- The Dynamics of Political Narratives During the Russian Invasion of Ukraine -- Anger Breeds Controversy: Analyzing Controversy and Emotions on Reddit -- Building a healthier feed: Private location trace intersection driven feed recommendations -- Classifying Policy Issue Frame Bias in Philippine Online News -- Dismantling Hate: Understanding Hate Speech Trends Against NBA Athletes -- Feedback Loops and Complex Dynamics of Harmful Speech in Online Discussions -- Chirping Diplomacy: Analyzing Chinese Social-Cyber Maneuvers on Twitter -- Vulnerability Dictionary: Language Use During Times of Crisis and Uncertainty -- Tracking China's Cross-Strait Bot Networks Against Taiwan -- Assessing Media's Representation of Frustration Towards Venezuelan Migrants in Colombia -- Human Behavior Modeling -- Agent-Based Moral Interaction Simulations in Imbalanced Polarized Settings -- Investigating the Use of Belief Bias to Measure Acceptance of False Information -- Simulation of Stance Perturbations -- Integrating Human Factors into Agent-Based Simulation for Dynamic Phishing Susceptibility -- Designing Organizations of Human and Non-Human Knowledge Workers -- Modeling Human Actions in the Cart-Pole Game Using Cognitive and Deep Reinforcement Learning Approach -- CCTFv1: Computational Modeling of Cyber Team Formation Strategies -- Simulating Transport Mode Choices in Developing Countries -- User Identity Modeling to Characterize Communication Patterns of Domestic Extremists Behavior on Social Media -- Understanding Clique Formation in Social Networks - An Agent-Based Model of Social Preferences in Fixed and Dynamic Networks -- A Bayesian Approach of Predicting the Movement of Internally Displaced Persons -- Social-Cyber Behavior Modeling -- Few-Shot Information Operation Detection Using Active Learning Approach -- Dynamic Modeling and Forecasting of Epidemics Incorporating Age and Vaccination Status -- Inductive Linear Probing for Few-shot Node Classification -- Regression Chain Model for Predicting Epidemic Variables -- Physical Distancing and Mask Wearing Behavior Dataset Generator from CCTV Footage Using YOLOv8 -- Moving Beyond Stance Detection in Cross-cutting Communication Analysis -- Pandemic Personas: Analyzing Identity Signals in COVID-19 Discourse on Twitter.

This book constitutes the proceedings of the 16th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2023, which was held in Pittsburgh, PA, USA in September 2023. The 31 full papers presented in this volume were carefully reviewed and selected from 73 submissions. The papers were organized in topical sections as follows: Detecting malign influence; human behavior modeling; and social-cyber behavior modeling

The Jack Voltaic (JV) Cyber Research project is an innovative, bottom-up approach to critical infrastructure resilience that informs our understanding of existing cybersecurity capabilities and identifies gaps. JV 3.0 contributed to a repeatable framework cities and municipalities nationwide can use to prepare. This report on JV 3.0 provides findings and recommendations for the military, federal agencies, and policy makers.