{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":22,"n_cols":5,"rows_kept":22,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[10,2,10,3],[11,2,11,3],[13,2,13,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNISA996464407403316"]
[null,null,"Titolo",null,"Social, cultural, and behavioral modeling : 14th international conference, SBP-BRiMS 2021, virtual event, July 6-9, 2021, proceedings / / Robert Thomson [and three others], editors"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-80387-2"]
[null,null,"Descrizione fisica",null,"1 online resource (353 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science ; ; 12720"]
[null,null,"Disciplina",null,"302.231"]
[null,null,"Soggetti",null,"Online social networks - Psychological aspects"]
[{"$nulls":4},"Interpersonal relations"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"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 "]
[{"$nulls":4},"Experiments -- 4.1 Dataset Description -- 4.2 Results -- 5 Conclusion -- References -- Mining Online Social Media to Drive Psychologically Valid Agent Models of Regional Covid-19 Mask Wearing -- Abstract -- 1 Introduction -- 2 Data -- 2.1 Mask-Wearing Data -- 2.2 CMU CASOS/IDeaS COVID-19 Twitter Data."]
[{"$nulls":4},"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."]
[{"$nulls":4},"GPU Accelerated PMCMC Algorithm with System Dynamics Modelling -- 1 Introduction -- 2 Background and Related Work -- 2.1 Particle Markov Chain Monte Carlo Methods and Parallelization -- 2.2 GPU Programming and CUDA -- 3 Implementation -- 4 Using Particle MCMC in Influenza Model Inference -- 4.1 Model Description -- 4.2 Model Inference Results -- 5 Experiments and Results -- 6 Discussion -- References -- An Analysis of Global News Coverage of Refugees Using a Big Data Approach -- 1 Refugees and Other Displaced Persons in the Media -- 2 Methodology -- 2.1 Dataset -- 2.2 Data Query -- 2.3 Limitations -- 3 Global News About Refugees -- 3.1 Refugee-Related Events Associated with Peak Coverage -- 3.2 Observing the Content CAMEO Codes of Refugee Related News -- 4 Discussion -- References -- An Identity-Based Framework for Generalizable Hate Speech Detection -- 1 Introduction -- 2 Data and Methods -- 2.1 Dataset Curation -- 2.2 An Identity Lexicon with Psycholinguistic Features -- 2.3 Problem Formulation and Experimental Setup -- 3 Results -- 3.1 Hate Speech Consistently Features Identity Abuse -- 3.2 Evaluating Identity Abuse for Hate Speech Detection -- 3.3 Mapping Cross-dataset Generalizability -- 4 Conclusions and Future Work -- References -- Using Diffusion of Innovations Theory to Study Connective Action Campaigns -- 1 Introduction -- 2 Literature Review -- 3 Data Collection and Research Methodology -- 4 Analysis and Results -- 5 Conclusions and Future Work -- References -- Reinforcement Learning for Data Poisoning on Graph Neural Networks -- 1 Introduction -- 2 Background -- 2.1 Preliminaries -- 2.2 Related Work -- 3 Motivation "]
[{"$nulls":4},"-- 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."]
[{"$nulls":4},"7 Future Work -- References -- Social Cybersecurity and Social Networks -- Simulating Social-Cyber Maneuvers to Deter Disinformation Campaigns -- 1 Introduction -- 2 Related Works -- 2.1 Modeling Information and Beliefs -- 2.2 BEND Framework -- 2.3 Modeling Emotions and Reason -- 3 Model Description -- 3.1 Review of twitter_sim Features -- 3.2 Model Changes Introduced for twitter_sim2.0 -- 4 Experiments -- 4.1 Network Based Maneuvers -- 4.2 Information Based Maneuvers -- 5 Results and Discussion -- 5.1 Baseline -- 5.2 Network Maneuver -- 5.3 Information Maneuver -- 6 Validation -- 7 Conclusion -- References -- Studying the Role of Social Bots During Cyber Flash Mobs -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Analysis -- 4 Results and Analysis -- 5 Conclusion and Future Research Directions -- References -- The Integrated Game Transformation Framework and Cyberwar: What 2×2 Games Tell Us About Cyberattacks -- 1 Introduction -- 2 Game Theory and Cyberwarfare -- 3 Methodology -- 3.1 The Integrated GTF Model -- 4 Findings -- 5 Discussion and Conclusion -- References -- Bot-Based Emotion Behavior Differences in Images During Kashmir Black Day Event -- 1 Introduction -- 2 Data and Methodology -- 2.1 Data Collection and Processing -- 2.2 Bot-Based Emotion Behavior Differences -- 2.3 Community Case Study -- 3 Results -- 3.1 Image Clusters in Kashmir's Black Day -- 3.2 Community Case Study -- 4 Discussion -- 5 Conclusion -- References -- Using Social Network Analysis to Analyze Development Priorities of Moroccan Institutions -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Dictionary Generation -- 3.2 Concern Identification -- 3.3 Network Generation -- 3.4 Evaluation -- 4 Results -- 5 Conclusion -- References -- Influence Dynamics Among Narratives -- 1 Introduction -- 2 Related Works -- 3 Data."]
[{"$nulls":4},"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 "]
[{"$nulls":4},"Formulation -- 3 Simulation Setup and Measurements -- 4 Results and Discussion -- 4.1 Scenario 1 -- 4.2 Scenario 2 -- 5 Conclusion -- References -- Having a Bad Day? Detecting the Impact of Atypical Events Using Wearable Sensors."]
[{"$nulls":4},"1 Introduction."]