<P>MSN BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES<BR><BR><STRONG>Introduction to Mobile Social Networking and Computing<BR></STRONG>Introduction<BR>Research and Application Framework of MSNs<BR>Structure and Interaction Perspective about MSNs<BR> Multidimensional Structure-Economic and Social Characteristics of MSNs<BR> Evolutionary Interaction<BR>MSN from an Application Perspective <BR> Socially Inspired Mobile Networking<BR> Enhanced Social Life with Mobile Technologies<BR>Fundamental Issues<BR> Incentive Mechanisms<BR> Trust and Reputation<BR> Identity Management and Privacy<BR> Location Technologies and Energy Efficiency<BR> HCI Issues<BR>Conclusion<BR>References<BR><BR>FUNDAMENTAL THEORY AND KEY PROBLEMS IN MSNs<BR><BR><STRONG>Multidimensional (Temporal-Spatio-Social) Structural Characteristics of Mobile Social Networks<BR></STRONG>Introduction<BR>Background on Static Social Network Characteristics and Measurements<BR> Degree Distribution<BR> Characteristic Path Length<BR> Clustering Coefficient<BR> Network Efficiency, E(G)<BR> Small-World Behavior<BR> Centrality<BR> Degree Centrality<BR> Closeness Centrality<BR> Betweenness Centrality<BR> Eigenvector Centrality<BR>Characterizing Time-Varying MSNs<BR> Classifying Temporal Information<BR> Static versus Temporal Analysis<BR> Evolving versus Temporal Networks<BR> Formalism in TVGs<BR> Journeys and Related Temporal Concepts<BR> Temporal Betweenness Centrality<BR> Temporal Closeness Centrality<BR> Temporal Eigenvector Centrality<BR> Small-World Properties in Temporal Social Network<BR> An Incarnation of TVG Framework<BR>Spatiosocial Characteristics of MSNs<BR> Node Locality<BR> Geographic Clustering Coefficient<BR>Conclusion<BR>References<BR><B><BR>User Behaviors and Interaction in MSNs<BR></B>Introduction<BR>Measuring and Characterizing User Interaction in MSNs<BR> Methodology of Measuring Users' Behaviors and Interactions<BR> Crowdsourcing-Based Measurement Architecture<BR> Experience Sampling Method for MSNs<BR> Various Features of Interactions in MSNs<BR> Connectivity and Interaction in Social Network<BR> Traffic Activities in Social Networks<BR> Locality of Interest and Navigation Characteristics<BR> Prediction of User Behavior in MSNs<BR> Prediction of User's Future Activity Level<BR> Geographical Prediction in MSN/OSN<BR>Modeling User Interactions in MSNs<BR> Multidimensional Characterizing of Human Mobility in MSNs<BR> An Integrated Behavior Model in MSNs<BR> Edge Creation<BR> Social Triadic Closure<BR> Triangle-Closing Models<BR> Mobility-Driven Closure<BR> Temporal Evolution<BR> Putting It All Together: New Models Emerging <BR>Motivating User Interaction in MSNs<BR>Conclusion<BR>References<BR><BR><B>Incentive Mechanisms in Mobile Social Networks<BR></B>Introduction<BR>Basic Concepts about Motivation Theories<BR> Motivation Approaches<BR> Economic View of Motivation: Example Design and Challenges<BR> Some Challenges in an Economic View of Motivation<BR> Behavioral Economics View of Motivation<BR> Motivation Theory from Psychology<BR> Future Trends<BR> Exploring Designs of Mechanisms Inspired by Theories of Motivation<BR> Personalized Incentive Mechanism Design<BR>Typical Incentive Schemes in MSNs<BR>Mobile Crowdsourcing Sensing in MSNs<BR>Conclusion and Future Directions<BR>References</P><P><B>Information Diffusion in Mobile Social Networks<BR></B>Introduction<BR>Information Diffusion Models<BR> General Threshold Model<BR> General Cascade Model<BR> Game Theory-Based Diffusion Model 5.3 Influence Maximization Problem<BR> Definition<BR> Existing Algorithms in Influence Maximization<BR> Greedy-Based Algorithms<BR> Heuristic Schemes<BR> Distributed Realization of Influence Maximization in MSNs<BR> Basic Concepts about Random Walk<BR> The Process of Distributed iWander Protocol Inspired by Random Walk<BR> The Evaluation of iWander<BR>Extensions to Influence Maximization<BR> Budget and Cost in Information Diffusion<BR> Competitive Information Diffusion<BR> Time-Critical Influence Maximization<BR>Conclusion<BR>References<BR><BR><B>Mobile Search and Ranking<BR></B>Introduction<BR>Some Challenges of Search and Ranking in MSNs<BR> Technological Factors<BR> Socioeconomic Factors<BR>Existing Schemes of Search and Ranking in MSNs<BR> A Preference-Enabled Querying Mechanism<BR> Related Work<BR> Architecture and Components<BR> Social Search Browser<BR> SSB Prototype<BR> Mobile Application<BR> Interactive Filters<BR> &nbsp