Social Computing and Behavioral Modeling (eBook)

Huan Liu, John Salerno, Michael J. Young (Herausgeber)

eBook Download: PDF

2009 | 2009
XVI, 264 Seiten
Springer US (Verlag)
978-1-4419-0056-2 (ISBN)

Infos

Social computing is concerned with the study of social behavior and social c- text based on computational systems. Behavioral modeling reproduces the social behavior, and allows for experimenting, scenario planning, and deep understa- ing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies provides an unprecedented environment of various - cial activities. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, and prediction. Numerous interdisciplinary and inter- pendent systems are created and used to represent the various social and physical systems for investigating the interactions between groups, communities, or nati- states. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines, social computing, and behavioral modeling in order to document lessons learned and develop novel theories, experiments, and methodo- gies in terms of social, physical, psychological, and governmental mechanisms. The goal is to enable us to experiment, create, and recreate an operational environment with a better understanding of the contributions from each individual discipline, forging joint interdisciplinary efforts. This is the second international workshop on Social Computing, Behavioral ModelingandPrediction. The submissions were from Asia, Australia, Europe, and America. Since SBP09 is a single-track workshop, we could not accept all the good submissions. The accepted papers cover a wide range of interesting topics.

Inhalt

Preface 5
Acknowledgements 7
Contents 8
List of Contributors 12
Organizing Committee 14
Program Committee 14
Reality Mining of Mobile Communications: Toward A New Deal On Data 16
References 16
Lifting Elephants: Twitter and Blogging in Global Perspective 17
1 Introduction 17
References 22
Rule Evaluation Model as Behavioral Modeling of Domain Experts 23
1 Introduction 23
2 Rule Evaluation Support with Rule Evaluation Models Based on Objective Indices 24
3 A Case Study on Chronic Hepatitis Data Mining Results 25
3.1 Description of the Chronic Hepatitis Data Mining Results 26
3.2 Comparison of the classification performances 27
3.3 Rule evaluation models for the data mining result datasets of chronic hepatitis 28
4 Conclusion 29
References 30
Trust and Privacy in Distributed Work Groups 31
Denise Anthony1, Tristan Henderson2, and James Kitts3 31
USA 31
Scotland, UK 31
1 Introduction 31
2 Trust, Cooperation and Work Teams 32
3 Methods 33
3 Results 34
Subject Privacy Preferences 5 Discussion and Conclusion 36
References 37
Cultural Consensus Theory: Aggregating Expert Judgments about Ties in a Social Network 39
1 Cultural Consensus Theory 39
2 A CCT Model for Aggregating Digraphs 41
2.1 Notation 41
2.2 The Consensus Model 42
2.3 Parameter Estimation 43
2.4 Interpreting Parameters 44
. 45
2.5 Possible Extensions 45
References 46
Dynamic Networks: Rapid Assessment of Changing Scenarios 48
1 Introduction 48
2 Criteria for Dynamic Distributed Network Analytics 49
3 Enhanced NRLs and Dynamic Battlefield Analysis 52
5 Concluding Remarks 55
References 55
Modeling Populations of Interest in Order to Simulate Cultural Response to Influence Activities 57
1 Societal Assessment Capability 57
2 High-Definition Cognitive Models 59
3 Systems Dynamics-based Aggregate Societal Model 60
4 Societal Assessment Prototype 61
5 Conclusion 63
References 64
The Use of Agent-based Modeling in Projecting Risk Factors into the Future 65
1 Introduction 65
2 Projecting HIV Factors into the Future 66
3 Projecting the Effects of Drug Busts on the Dynamics of the Heroin Market 68
4 Discussion 69
References 70
Development of an Integrated Sociological Modeling Framework (ISMF) to Model Social Systems 71
1 Introduction 1.1 Terms 71
1.2 Background 72
2 Methodology 2.1 Joint Application Development (JAD) Process 72
2.2 Mind Mapping 74
2.3 Use Case Modeling 75
3 Enhanced Joint Application Development (E-JAD) 76
4 Object-Oriented Analysis and Design (OOAD) 76
5 Integrated Sociological Modeling Framework (ISMF) 78
5.1 Example Social Study: Preconception Peer Education Program (PPPEP) 79
References 81
The Coherence Model of Preference and Belief Formation 82
1 Introduction 82
2 Specifying the Model 84
4 Conclusion 88
References 89
Cognitive Modeling of Household Economic Behaviors during Extreme Events 91
1 Introduction 91
2 The Cognitive-Economic Model1 92
3.0 Large-Scale Behavioral Modeling of Food Purchasing During a Pandemic Influenza 94
4.0 Summary and Conclusions 97
References 99
Collaborating with Multiple Distributed Perspectives and Memories 100
1 Introduction 100
2 Distributed Episodic Memory 101
3 Memory and Cultural Models 102
4 Maintaining Coherence 103
5 Experimental Results 104
6 Conclusion 106
References 107
When is social computation better than the sum of its parts? 108
1 Introduction 108
2 Information theory approach to stochastic search 110
2.1 Synergy and Redundancy 110
2.2 Two-dimensional spatial search 110
3 Correlated stochastic source and synergy of searchers 112
3.1 Uncorrelated signals: Poisson source 112
3.2 Correlated signals: angular biases 113
4 Conclusion 114
References 115
The Dilemma of Social Order in Iraq 117
2 Forms of Governance and Social Order in Iraq 118
2 Implications for Social Order in Present-day Iraq 123
References 126
A Socio-Technical Approach to Understanding Perceptions of Trustworthiness in Virtual Organizations 128
1 Introduction 128
2 Problem-based Question 129
3 Theoretical Frameworks 130
4 Method 132
4.1 Factorial Design 133
4.2 Variables 133
4.3 Hypotheses 134
5 Preliminary Discussions 135
6 Conclusions and Future Work 136
References 137
Prior-free cost sharing design: group strategyproofness and the worst absolute loss 138
1 Introduction 138
2 Single facility location problem 139
3 Generalized scheduling problem 141
4 More general results and related literature 142
5 Open problems 143
References 144
Monitoring Web Resources Discovery by Reusing Classification Knowledge 145
1 Introduction 145
2 Related Studies 146
3 Research Design 147
4 Experimental Results 148
5 Conclusions 151
Acknowledgement 152
References 152
Finding Influential Nodes in a Social Network from Information Diffusion Data 153
1 Introduction 153
2 Proposed Method 2.1 Problem Formulation and Extraction Method 154
2.2 Probability Estimation Method 155
3 Experiments 3.1 Experimental Settings 156
3.2 Comparison Methods 156
3.3 Experimental Results 157
4 Discussion 158
5 Conclusion 159
References 160
Meta-modeling the Cultural Behavior Using Timed Influence Nets 161
1 Introduction 161
2 Architecture 164
Component Description 164
3 Application 165
Compo-nent Description Template Ontology Template TIN 167
Compo-nent Description Mapping Box 168
Derived TIN 4 Conclusion 168
References 169
A Validation Process for Predicting Stratagemical Behavior Patterns of Powerful Leaders in Conflict 170
1. Introduction 170
2. The Belief Model Validation Process 171
3. The PMESII-PT Elements and the Operational Environment 173
4. The Powerful Leader Belief Model 174
5. Technosocial Factors Affecting Powerful Leader Stratagemical Behavior Patterns 176
6. Implications and Conclusions 177
References 177
Control of Opinions in an Ideologically Homogeneous Population 178
1 Introduction 178
2 Complete Network 180
2.1 Uniformly Distributed e 180
2.2 Normally distributed e 180
3 Scale Free Network 182
3.1 Uniformly Distributed e 183
3.2 Normally Distributed e 184
3.3 Targeting High Degree Nodes 184
4 Conclusion 185
References 186
Estimating Cyclic and Geospatial Effects of Alcohol Usage in a Social Network Directed Graph Model 187
1 Introduction 187
2 Estimating Temporal and Cyclic Effects 187
3 Estimating Geospatial Effects 191
4 Conclusions 193
Acknowledgements 194
References 194
HBML: A Language for Quantitative Behavioral Modeling in the Human Terrain 195
1 Introduction 195
2 Language Overview 196
3 Glossary of Terms and Concepts 197
4 Anomaly Detection, Classification, and Prediction in HBML 199
4.1 Background: Terrorist Suspects in the Human Terrain 200
5 Conclusion 204
Acknowledgements 204
References 204
VIM: A Platform for Violent Intent Modeling 205
1 Introduction 205
2 Background 206
3 The VIM Approach 207
4 Social Science Guidance Map 208
5 Content Extraction and Analysis 210
6 Bayesian Analysis of Competing Hypotheses 211
7 The VIM Software Platform 212
8 Conclusions 214
References 214
Punishment, Rational Expectations, and Relative Payoffs in a Networked Prisoners Dilemma 216
1 Introduction 216
2 The Simulation 217
2.1 The Continuous Prisoners Dilemma 217
2.2 Altruistic Punishment 218
2.3 Social Structure 218
2.4 The Simulation Algorithm 219
3 The Model of Relative Payoff Maximization 220
4 Results and Discussion 221
4.1 Occurrence of Punishment 221
4.2 Punishment and number of neighbors 222
5 Summary 222
References 223
A Network-Based Approach to Understanding and Predicting Diseases 224
1 Introduction 224
2 Data 225
3 Properties of the Disease Network 226
4 Disease Prediction in the Patient Network 228
5 Conclusion 231
References 231
Status and Ethnicity in Vietnam: Evidence from Experimental Games 232
References 233
Behavior Grouping based on Trajectory Mining 234
1 Introduction 234
2 Method 2.1 Multiscale Description of Trajectories by the Modified Bessel Function 235
2.2 Segment Hierarchy Trace and Matching 236
2.3 Local Segment Difference 237
( 238
) 238
( a 238
) 238
g a 238
2.4 Sequence Dissimilarity 238
2.5 Clustering 239
3 Experimental Results 239
4 Conclusions 241
References 241
Learning to Recommend Tags for On-line Photos 242
1 Introduction 242
2 Semantic Image-Tag Correlation Analysis via KCCA 243
: (x=x,..., xm) .. x)=( x),..., ( , 244
3 Tag Recommendation: the Proposed Approach 244
3.1 Tag Ranking 244
S c / max{c } (9) 246
= 246
4 Experiments and Results 246
5 Conclusion and Future Work 249
References 249
A Social Network Model of Alcohol Behaviors 251
1 Introduction 251
2 Building the Model 252
3 Choosing the Agents 253
4 Conclusions 257
Acknowledgements 257
References 257
Using Participatory Learning to Model Human Behavior 259
1 Introduction 259
2 The Participatory Learning Paradigm 260
3 A Basic Participatory Learning Model 263
4 Learning From Interval Observations 264
5 Conclusion 267
References 267
Biographies 269
Author Index 271

Produkt-Details

• Erscheint lt. Verlag: 5.4.2009
• Zusatzinfo: XVI, 264 p. 100 illus.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Informatik ► Datenbanken ► Data Warehouse / Data Mining
• Themenwelt: Informatik ► Office Programme ► Outlook
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung
• Themenwelt: Technik
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Planung / Organisation
• Schlagworte: classification • computational cultural study • Computer • Evaluation • group profiling and interaction • Modeling • pattern mining • Sage • simulation with social media
• ISBN-10: 1-4419-0056-X / 144190056X
• ISBN-13: 978-1-4419-0056-2 / 9781441900562