10964nam 2200517 450 99646440740331620220325093536.03-030-80387-2(CKB)5590000000523718(MiAaPQ)EBC6668449(Au-PeEL)EBL6668449(OCoLC)1259439332(PPN)257358854(EXLCZ)99559000000052371820220325d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierSocial, cultural, and behavioral modeling 14th international conference, SBP-BRiMS 2021, virtual event, July 6-9, 2021, proceedings /Robert Thomson [and three others], editorsCham, Switzerland :Springer,[2021]©20211 online resource (353 pages)Lecture Notes in Computer Science ;127203-030-80386-4 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.2.3 Twitter Coronavirus (COVID-19) Geo-Tagged Tweets Dataset -- 3 Pro/Con Tweets/Retweets in Four States -- 4 Stance Detection -- 5 Psychologically Valid Agents (PVAs) -- 5.1 Dynamics of Attitudes and Infection -- 5.2 Match to Data -- 6 Conclusion -- Acknowledgements -- References -- Fine-Grained Analysis of the Use of Neutral and Controversial Terms for COVID-19 on Social Media -- 1 Introduction -- 2 Related Work -- 3 Data and Methodology -- 3.1 Data Collection and Pre-processing -- 3.2 Classification -- 3.3 Latent Dirichlet Allocation -- 3.4 LIWC2015 -- 4 Empirical Results -- 4.1 Classification -- 4.2 LDA -- 4.3 LIWC Sentiment Features -- 5 Conclusion -- References -- Methodologies -- Assessing Bias in YouTube's Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context -- 1 Introduction -- 2 Related Work -- 3 Datasets and Data Collection Methodology -- 4 Experiments and Findings -- 4.1 Bias Detection -- 4.2 Bias Variance -- 4.3 Findings -- 5 Conclusions and Future Work -- References -- Formal Methods for an Iterated Volunteer's Dilemma -- 1 Introduction -- 2 Background -- 2.1 The Volunteer's Dilemma -- 3 Design Overview -- 3.1 Game Parameters -- 3.2 Action Space -- 3.3 Reward Structure -- 4 Experiments and Results -- 4.1 Model Correctness -- 4.2 Property Verification -- 4.3 Reward Maximization -- 5 Limitations and Future Work -- 6 Conclusion -- References -- Privacy Preserving Text Representation Learning Using BERT -- 1 Introduction -- 2 Problem Statement -- 3 The Proposed Framework -- 3.1 Sentence Representation Using BERT -- 3.2 Perturbing Text by Adding Noise -- 3.3 Preserving Text Utility -- 3.4 Protecting Private Information -- 3.5 DPBERT - Learning the Text Representation -- 4 Experiments -- 4.1 Data -- 4.2 Experimental Design -- 4.3 Experimental Result -- 5 Related Work -- 6 Conclusion -- References.GPU Accelerated PMCMC Algorithm with System Dynamics Modelling -- 1 Introduction -- 2 Background and Related Work -- 2.1 Particle Markov Chain Monte Carlo Methods and Parallelization -- 2.2 GPU Programming and CUDA -- 3 Implementation -- 4 Using Particle MCMC in Influenza Model Inference -- 4.1 Model Description -- 4.2 Model Inference Results -- 5 Experiments and Results -- 6 Discussion -- References -- An Analysis of Global News Coverage of Refugees Using a Big Data Approach -- 1 Refugees and Other Displaced Persons in the Media -- 2 Methodology -- 2.1 Dataset -- 2.2 Data Query -- 2.3 Limitations -- 3 Global News About Refugees -- 3.1 Refugee-Related Events Associated with Peak Coverage -- 3.2 Observing the Content CAMEO Codes of Refugee Related News -- 4 Discussion -- References -- An Identity-Based Framework for Generalizable Hate Speech Detection -- 1 Introduction -- 2 Data and Methods -- 2.1 Dataset Curation -- 2.2 An Identity Lexicon with Psycholinguistic Features -- 2.3 Problem Formulation and Experimental Setup -- 3 Results -- 3.1 Hate Speech Consistently Features Identity Abuse -- 3.2 Evaluating Identity Abuse for Hate Speech Detection -- 3.3 Mapping Cross-dataset Generalizability -- 4 Conclusions and Future Work -- References -- Using Diffusion of Innovations Theory to Study Connective Action Campaigns -- 1 Introduction -- 2 Literature Review -- 3 Data Collection and Research Methodology -- 4 Analysis and Results -- 5 Conclusions and Future Work -- References -- Reinforcement Learning for Data Poisoning on Graph Neural Networks -- 1 Introduction -- 2 Background -- 2.1 Preliminaries -- 2.2 Related Work -- 3 Motivation -- 4 Methodology -- 4.1 Data Procurement -- 4.2 Graph Classification -- 4.3 Graph Neural Networks -- 4.4 Reinforcement Learning -- 4.5 Poison Attack -- 5 Experiments -- 5.1 MiniGCDataset -- 5.2 MiniGC - Larger -- 6 Conclusion.7 Future Work -- References -- Social Cybersecurity and Social Networks -- Simulating Social-Cyber Maneuvers to Deter Disinformation Campaigns -- 1 Introduction -- 2 Related Works -- 2.1 Modeling Information and Beliefs -- 2.2 BEND Framework -- 2.3 Modeling Emotions and Reason -- 3 Model Description -- 3.1 Review of twitter_sim Features -- 3.2 Model Changes Introduced for twitter_sim2.0 -- 4 Experiments -- 4.1 Network Based Maneuvers -- 4.2 Information Based Maneuvers -- 5 Results and Discussion -- 5.1 Baseline -- 5.2 Network Maneuver -- 5.3 Information Maneuver -- 6 Validation -- 7 Conclusion -- References -- Studying the Role of Social Bots During Cyber Flash Mobs -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Analysis -- 4 Results and Analysis -- 5 Conclusion and Future Research Directions -- References -- The Integrated Game Transformation Framework and Cyberwar: What 2×2 Games Tell Us About Cyberattacks -- 1 Introduction -- 2 Game Theory and Cyberwarfare -- 3 Methodology -- 3.1 The Integrated GTF Model -- 4 Findings -- 5 Discussion and Conclusion -- References -- Bot-Based Emotion Behavior Differences in Images During Kashmir Black Day Event -- 1 Introduction -- 2 Data and Methodology -- 2.1 Data Collection and Processing -- 2.2 Bot-Based Emotion Behavior Differences -- 2.3 Community Case Study -- 3 Results -- 3.1 Image Clusters in Kashmir's Black Day -- 3.2 Community Case Study -- 4 Discussion -- 5 Conclusion -- References -- Using Social Network Analysis to Analyze Development Priorities of Moroccan Institutions -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Dictionary Generation -- 3.2 Concern Identification -- 3.3 Network Generation -- 3.4 Evaluation -- 4 Results -- 5 Conclusion -- References -- Influence Dynamics Among Narratives -- 1 Introduction -- 2 Related Works -- 3 Data.4 Methodology -- 4.1 Multi-Variate Hawkes Processes -- 4.2 Quantifying and Comparing Influence Effects -- 5 Results and Discussion -- References -- Network Structures and Humanitarian Need -- 1 Introduction -- 2 Humanitarian Response as a Network -- 2.1 Measuring Network Robustness -- 2.2 The International Aid Regime -- 3 Methodology -- 3.1 Data and Limitations -- 3.2 Measurements -- 4 Humanitarian Aid Under Stress -- 4.1 Divergent Donor Typologies -- 4.2 Addressing Changing Needs -- 5 Discussion -- References -- Identifying Shifts in Collective Attention to Topics on Social Media -- 1 Introduction -- 2 Related Works -- 3 Methods and Materials -- 4 Data -- 5 Experiments and Results -- 6 Conclusions -- References -- wapr.tugon.ph: A Secure Helpline for Detecting Psychosocial Aid from Reports of Unlawful Killings in the Philippines -- 1 Introduction -- 2 Review of Related Literature -- 2.1 Origins of wapr.tugon.ph -- 2.2 Providing Psychosocial Intervention During Crisis -- 2.3 Digital Psychosocial Intervention -- 2.4 Natural Language Processing Text Classification for Detecting Elements of Psychosocial Wellbeing -- 2.5 Securing Human Rights Violation Reports and Data Admissibility Through Blockchain -- 3 Framework and Methodology -- 3.1 warp.tugon.ph Architecture -- 3.2 Psychosocial Wellness Detection Model -- 4 Results and Discussion -- 4.1 Features and Functionalities of wapr.tugon.ph -- 4.2 Psychosocial Wellness Detection Model Performance -- 5 Conclusion -- References -- Human and Agent Modeling -- Social-Judgment-Based Modeling of Opinion Polarization in Chinese Live Streaming Platforms -- 1 Introduction -- 2 Model Formulation -- 3 Simulation Setup and Measurements -- 4 Results and Discussion -- 4.1 Scenario 1 -- 4.2 Scenario 2 -- 5 Conclusion -- References -- Having a Bad Day? Detecting the Impact of Atypical Events Using Wearable Sensors.1 Introduction.Lecture notes in computer science ;12720.Online social networksPsychological aspectsCongressesInterpersonal relationsCongressesOnline social networksPsychological aspectsInterpersonal relations302.231Thomson RobertMiAaPQMiAaPQMiAaPQBOOK996464407403316Social, Cultural, and Behavioral Modeling2010766UNISA02648nam 2200637I 450 991070703470332120160329123309.0(CKB)5470000002461143(OCoLC)945658267(EXLCZ)99547000000246114320160329j199607 ua 0engurbn|||||||||txtrdacontentcrdamediacrrdacarrierFriction and wear characteristics of candidate foil bearing materials from 25 °C to 800 °C /J.A. Laskowski and C. DellaCorteCleveland, Ohio :National Aeronautics and Space Administration, Lewis Research Center,July 1996.1 online resource (18 pages) illustrationsNASA/TM ;107082Title from title screen (viewed March 29, 2016)."July 1996.""Work performed for U.S. Department of Energy, Conservation and Renewable Energy, Office of Vehicle and Engine R&D.""Prepared for the Annual Meeting sponsored by the Society of Tribologists and Lubrication Engineers, Cincinnati, Ohio, May 19-23, 1996.""Performing organization: National Aeronautics and Space Administration, Lewis Research Center, Cleveland, Ohio"--Report documentation page.Includes bibliographical references (pages 11-12).Friction and wear characteristics of candidate foil bearing materials from 25 degree C to 800 degrees CFoil bearingsnasatInconel (trademark)nasatIron alloysnasatTribologynasatHigh temperature testsnasatSliding frictionnasatWear resistancenasatRene 41nasatAluminum oxidesnasatFoil bearings.Inconel (trademark)Iron alloys.Tribology.High temperature tests.Sliding friction.Wear resistance.Rene 41.Aluminum oxides.Laskowski J. A.1412796DellaCorte ChristopherUnited States.Department of Energy.Office of Vehicle and Engine Research and Development.Lewis Research Center,United States.National Aeronautics and Space Administration,GPOGPOBOOK9910707034703321Friction and wear characteristics of candidate foil bearing materials from 25 °C to 800 °C3507440UNINA